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Cloudera Data Platform (CDP)
Public Cloud service rates

The table below reflects hourly pricing for Cloudera Data Platform Public Cloud Services offerings. The prices reflected do not include infrastructure cost. Infrastructure pricing is available through the respective cloud providers.

 

  • Amazon Web Services
  • Microsoft Azure
  • Google Cloud Platform (GCP)

Data Engineering - AWS instances

Instance Category Cores vCPUs RAM GPU CCUs Core Rate/hr All-Purpose Rate/hr
m5.2xlarge General purpose 4 8 32 0.00 4.00 $0.2800 $0.8000
m5.4xlarge General purpose 8 16 64 0.00 8.00 $0.5600 $1.6000
m5.8xlarge General purpose 16 32 128 0.00 16.00 $1.1200 $3.2000
m5.16xlarge General purpose 32 64 256 0.00 32.00 $2.2400 $6.4000
m5.24xlarge General purpose 48 96 384 0.00 48.00 $3.3600 $9.6000
m5a.2xlarge General purpose 4 8 32 0.00 4.00 $0.2800 $0.8000
m5a.4xlarge General purpose 8 16 64 0.00 8.00 $0.5600 $1.6000
m5a.8xlarge General purpose 16 32 128 0.00 16.00 $1.1200 $3.2000
m5a.16xlarge General purpose 32 64 256 0.00 32.00 $2.2400 $6.4000
m5a.24xlarge General purpose 48 96 384 0.00 48.00 $3.3600 $9.6000
m5ad.2xlarge General purpose 4 8 32 0.00 4.00 $0.2800 $0.8000
m5ad.4xlarge General purpose 8 16 64 0.00 8.00 $0.5600 $1.6000
m5ad.8xlarge General purpose 16 32 128 0.00 16.00 $1.1200 $3.2000
m5ad.24xlarge General purpose 48 96 384 0.00 48.00 $3.3600 $9.6000
m5d.2xlarge General purpose 4 8 32 0.00 4.00 $0.2800 $0.8000
m5d.4xlarge General purpose 8 16 64 0.00 8.00 $0.5600 $1.6000
m5d.8xlarge General purpose 16 32 128 0.00 16.00 $1.1200 $3.2000
m5d.16xlarge General purpose 32 64 256 0.00 32.00 $2.2400 $6.4000
m5d.24xlarge General purpose 48 96 384 0.00 48.00 $3.3600 $9.6000
m6i.2xlarge General purpose 4 8 32 0.00 4.00 $0.2800 $0.8000
m6i.4xlarge General purpose 8 16 64 0.00 8.00 $0.5600 $1.6000
m6i.8xlarge General purpose 16 32 128 0.00 16.00 $1.1200 $3.2000
m6i.12xlarge General purpose 24 48 192 0.00 24.00 $1.6800 $4.8000
m6i.16xlarge General purpose 32 64 256 0.00 32.00 $2.2400 $6.4000
m6i.24xlarge General purpose 48 96 384 0.00 48.00 $3.3600 $9.6000
m6i.32xlarge General purpose 64 128 512 0.00 64.00 $4.4800 $12.8000
m6id.2xlarge General purpose 4 8 32 0.00 4.00 $0.2800 $0.8000
m6id.4xlarge General purpose 8 16 64 0.00 8.00 $0.5600 $1.6000
m6id.8xlarge General purpose 16 32 128 0.00 16.00 $1.1200 $3.2000
m6id.12xlarge General purpose 24 48 192 0.00 24.00 $1.6800 $4.8000
m6id.16xlarge General purpose 32 64 256 0.00 32.00 $2.2400 $6.4000
m6id.24xlarge General purpose 48 96 384 0.00 48.00 $3.3600 $9.6000
m6id.32xlarge General purpose 64 128 512 0.00 64.00 $4.4800 $12.8000
m6a.2xlarge General purpose 4 8 32 0.00 4.00 $0.2800 $0.8000
m6a.4xlarge General purpose 8 16 64 0.00 8.00 $0.5600 $1.6000
m6a.8xlarge General purpose 16 32 128 0.00 16.00 $1.1200 $3.2000
m6a.12xlarge General purpose 24 48 192 0.00 24.00 $1.6800 $4.8000
m6a.16xlarge General purpose 32 64 256 0.00 32.00 $2.2400 $6.4000
m6a.24xlarge General purpose 48 96 384 0.00 48.00 $3.3600 $9.6000
m6a.32xlarge General purpose 64 128 512 0.00 64.00 $4.4800 $12.8000
m6a.48xlarge General purpose 96 192 768 0.00 96.00 $6.7200 $19.2000
                 
r5.2xlarge Memory optimized 4 8 64 0.00 6.67 $0.4667 $1.3333
r5.4xlarge Memory optimized 8 16 128 0.00 13.33 $0.9333 $2.6667
r5.8xlarge Memory optimized 16 32 256 0.00 26.67 $1.8667 $5.3333
r5.16xlarge Memory optimized 32 64 512 0.00 53.33 $3.7333 $10.6667
r5.24xlarge Memory optimized 48 96 768 0.00 80.00 $5.6000 $16.0000
r5a.2xlarge Memory optimized 4 8 64 0.00 6.67 $0.4667 $1.3333
r5a.4xlarge Memory optimized 8 16 128 0.00 13.33 $0.9333 $2.6667
r5a.8xlarge Memory optimized 16 32 256 0.00 26.67 $1.8667 $5.3333
r5a.16xlarge Memory optimized 32 64 512 0.00 53.33 $3.7333 $10.6667
r5a.24xlarge Memory optimized 48 96 768 0.00 80.00 $5.6000 $16.0000
r5ad.2xlarge Memory optimized 4 8 64 0.00 6.67 $0.4667 $1.3333
r5ad.4xlarge Memory optimized 8 16 128 0.00 13.33 $0.9333 $2.6667
r5ad.8xlarge Memory optimized 16 32 256 0.00 26.67 $1.8667 $5.3333
r5ad.24xlarge Memory optimized 48 96 768 0.00 80.00 $5.6000 $16.0000
r5d.2xlarge Memory optimized 4 8 64 0.00 6.67 $0.4667 $1.3333
r5d.4xlarge Memory optimized 8 16 128 0.00 13.33 $0.9333 $2.6667
r5d.8xlarge Memory optimized 16 32 256 0.00 26.67 $1.8667 $5.3333
r5d.16xlarge Memory optimized 32 64 512 0.00 53.33 $3.7333 $10.6667
r5d.24xlarge Memory optimized 48 96 768 0.00 80.00 $5.6000 $16.0000
r6a.large Memory optimized 1 2 16 0.00 1.67 $0.1167 $0.3333
r6a.xlarge Memory optimized 2 4 32 0.00 3.33 $0.2333 $0.6667
r6a.2xlarge Memory optimized 4 8 64 0.00 6.67 $0.4667 $1.3333
r6a.4xlarge Memory optimized 8 16 128 0.00 13.33 $0.9333 $2.6667
r6a.8xlarge Memory optimized 16 32 256 0.00 26.67 $1.8667 $5.3333
r6a.12xlarge Memory optimized 24 48 384 0.00 40.00 $2.8000 $8.0000
r6a.16xlarge Memory optimized 32 64 512 0.00 53.33 $3.7333 $10.6667
r6a.24xlarge Memory optimized 48 96 768 0.00 80.00 $5.6000 $16.0000
r6a.32xlarge Memory optimized 64 128 1024 0.00 106.67 $7.4667 $21.3333
r6a.48xlarge Memory optimized 96 192 1536 0.00 160.00 $11.2000 $32.0000
r6i.2xlarge Memory optimized 4 8 64 0.00 6.67 $0.4667 $1.3333
r6i.4xlarge Memory optimized 8 16 128 0.00 13.33 $0.9333 $2.6667
r6i.8xlarge Memory optimized 16 32 256 0.00 26.67 $1.8667 $5.3333
r6i.12xlarge Memory optimized 24 48 384 0.00 40.00 $2.8000 $8.0000
r6i.16xlarge Memory optimized 32 64 512 0.00 53.33 $3.7333 $10.6667
r6i.24xlarge Memory optimized 48 96 768 0.00 80.00 $5.6000 $16.0000
r6i.32xlarge Memory optimized 64 128 1,024 0.00 106.67 $7.4667 $21.3333
r6id.2xlarge Memory optimized 4 8 64 0.00 6.67 $0.4667 $1.3333
r6id.4xlarge Memory optimized 8 16 128 0.00 13.33 $0.9333 $2.6667
r6id.8xlarge Memory optimized 16 32 256 0.00 26.67 $1.8667 $5.3333
r6id.12xlarge Memory optimized 24 48 384 0.00 40.00 $2.8000 $8.0000
r6id.16xlarge Memory optimized 32 64 512 0.00 53.33 $3.7333 $10.6667
r6id.24xlarge Memory optimized 48 96 768 0.00 80.00 $5.6000 $16.0000
r6id.32xlarge Memory optimized 64 128 1,024 0.00 106.67 $7.4667 $21.3333
                 
c5.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.1867 $0.5333
c5.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.3733 $1.0667
c5.9xlarge Compute optimized 18 36 72 0.00 12.00 $0.8400 $2.4000
c5.12xlarge Compute optimized 24 48 96 0.00 16.00 $1.1200 $3.2000
c5.24xlarge Compute optimized 48 96 192 0.00 32.00 $2.2400 $6.4000
c5ad.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.1867 $0.5333
c5ad.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.3733 $1.0667
c5a.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.1867 $0.5333
c5a.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.3733 $1.0667
c5d.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.1867 $0.5333
c5d.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.3733 $1.0667
c5d.9xlarge Compute optimized 18 36 72 0.00 12.00 $0.8400 $2.4000
c6i.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.1867 $0.5333
c6i.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.3733 $1.0667
c6i.8xlarge Compute optimized 16 32 64 0.00 10.67 $0.7467 $2.1333
c6i.12xlarge Compute optimized 24 48 96 0.00 16.00 $1.1200 $3.2000
c6i.16xlarge Compute optimized 32 64 128 0.00 21.33 $1.4933 $4.2667
c6i.24xlarge Compute optimized 48 96 192 0.00 32.00 $2.2400 $6.4000
c6i.32xlarge Compute optimized 64 128 256 0.00 42.67 $2.9867 $8.5333
c6id.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.1867 $0.5333
c6id.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.3733 $1.0667
c6id.8xlarge Compute optimized 16 32 64 0.00 10.67 $0.7467 $2.1333
c6id.12xlarge Compute optimized 24 48 96 0.00 16.00 $1.1200 $3.2000
c6id.16xlarge Compute optimized 32 64 128 0.00 21.33 $1.4933 $4.2667
c6id.24xlarge Compute optimized 48 96 192 0.00 32.00 $2.2400 $6.4000
c6id.32xlarge Compute optimized 64 128 256 0.00 42.67 $2.9867 $8.5333
c6a.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.1867 $0.5333
c6a.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.3733 $1.0667
c6a.8xlarge Compute optimized 16 32 64 0.00 10.67 $0.7467 $2.1333
c6a.12xlarge Compute optimized 24 48 96 0.00 16.00 $1.1200 $3.2000
c6a.16xlarge Compute optimized 32 64 128 0.00 21.33 $1.4933 $4.2667
c6a.24xlarge Compute optimized 48 96 192 0.00 32.00 $2.2400 $6.4000
c6a.32xlarge Compute optimized 64 128 256 0.00 42.67 $2.9867 $8.5333
c6a.48xlarge Compute optimized 96 192 384 0.00 64.00 $4.4800 $12.8000
                 
i3.2xlarge Storage optimized 4 8 61 0.00 6.42 $0.4492 $1.2833
i3.4xlarge Storage optimized 8 16 122 0.00 12.83 $0.8983 $2.5667
i3.8xlarge Storage optimized 16 32 244 0.00 25.67 $1.7967 $5.1333

 

Data Warehouse - AWS instances

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr
r5d.4xlarge Memory optimized 8 16 128 0 13.33 $0.9333
r5ad.4xlarge Memory optimized 8 16 128 0 13.33 $0.9333
r5dn.4xlarge Memory optimized 8 16 128 0 13.33 $0.9333
r6id.4xlarge Memory optimized 8 16 128 0 13.33 $0.9333

Machine Learning - AWS instances

InstanceCategoryCoresvCPUsRAMGPUCCUsRate/hr
m4.largeGeneral purpose12801.00$0.2000
m4.xlargeGeneral purpose241602.00$0.4000
m4.2xlargeGeneral purpose483204.00$0.8000
m4.4xlargeGeneral purpose8166408.00$1.6000
m4.10xlargeGeneral purpose2040160020.00$4.0000
m4.16xlargeGeneral purpose3264256032.00$6.4000
m5.largeGeneral purpose12801.00$0.2000
m5.xlargeGeneral purpose241602.00$0.4000
m5.2xlargeGeneral purpose483204.00$0.8000
m5.4xlargeGeneral purpose8166408.00$1.6000
m5.8xlargeGeneral purpose1632128016.00$3.2000
m5.12xlargeGeneral purpose2448192024.00$4.8000
m5.24xlargeGeneral purpose4896384048.00$9.6000
m5d.largeGeneral purpose12801.00$0.2000
m5d.xlargeGeneral purpose241602.00$0.4000
m5d.2xlargeGeneral purpose483204.00$0.8000
m5d.4xlargeGeneral purpose8166408.00$1.6000
m5d.12xlargeGeneral purpose2448192024.00$4.8000
m5d.24xlargeGeneral purpose4896384048.00$9.6000
m5a.largeGeneral purpose12801.00$0.2000
m5a.xlargeGeneral purpose241602.00$0.4000
m5a.2xlargeGeneral purpose483204.00$0.8000
m5a.4xlargeGeneral purpose8166408.00$1.6000
m5a.8xlargeGeneral purpose1632128016.00$3.2000
m5a.12xlargeGeneral purpose2448192024.00$4.8000
m5a.16xlargeGeneral purpose3264256032.00$6.4000
m5a.24xlargeGeneral purpose4896384048.00$9.6000
m6a.xlargeGeneral purpose241602.00$0.4000
m6a.2xlargeGeneral purpose483204.00$0.8000
m6a.4xlargeGeneral purpose8166408.00$1.6000
m6a.8xlargeGeneral purpose1632128016.00$3.2000
m6a.12xlargeGeneral purpose2448192024.00$4.8000
m6a.16xlargeGeneral purpose3264256032.00$6.4000
m6a.24xlargeGeneral purpose4896384048.00$9.6000
m6a.32xlargeGeneral purpose64128512064.00$12.8000
m6a.48xlargeGeneral purpose96192768096.00$19.2000
m6i.xlargeGeneral purpose241602.00$0.4000
m6i.2xlargeGeneral purpose483204.00$0.8000
m6i.4xlargeGeneral purpose8166408.00$1.6000
m6i.8xlargeGeneral purpose1632128016.00$3.2000
m6i.12xlargeGeneral purpose2448192024.00$4.8000
m6i.16xlargeGeneral purpose3264256032.00$6.4000
m6i.24xlargeGeneral purpose4896384048.00$9.6000
m6i.32xlargeGeneral purpose64128512064.00$12.8000
m6id.xlargeGeneral purpose241602.00$0.4000
m6id.2xlargeGeneral purpose483204.00$0.8000
m6id.4xlargeGeneral purpose8166408.00$1.6000
m6id.8xlargeGeneral purpose1632128016.00$3.2000
m6id.12xlargeGeneral purpose2448192024.00$4.8000
m6id.16xlargeGeneral purpose3264256032.00$6.4000
m6id.24xlargeGeneral purpose4896384048.00$9.6000
m6id.32xlargeGeneral purpose64128512064.00$12.8000
        
r3.xlargeMemory optimized243103.25$0.6500
r3.2xlargeMemory optimized486106.42$1.2833
r3.4xlargeMemory optimized816122012.83$2.5667
r3.8xlargeMemory optimized1632244025.67$5.1333
r4.xlargeMemory optimized243103.25$0.6500
r4.2xlargeMemory optimized486106.42$1.2833
r4.4xlargeMemory optimized816122012.83$2.5667
r4.8xlargeMemory optimized1632244025.67$5.1333
r4.16xlargeMemory optimized3264488051.33$10.2667
r5.largeMemory optimized121601.67$0.3333
r5.xlargeMemory optimized243203.33$0.6667
r5.2xlargeMemory optimized486406.67$1.3333
r5.4xlargeMemory optimized816128013.33$2.6667
r5.8xlargeMemory optimized1632256026.67$5.3333
r5.12xlargeMemory optimized2448384040.00$8.0000
r5.16xlargeMemory optimized3264512053.33$10.6667
r5.24xlargeMemory optimized4896768080.00$16.0000
r5d.largeMemory optimized121601.67$0.3333
r5d.xlargeMemory optimized243203.33$0.6667
r5d.2xlargeMemory optimized486406.67$1.3333
r5d.4xlargeMemory optimized816128013.33$2.6667
r5d.12xlargeMemory optimized2448384040.00$8.0000
r5d.24xlargeMemory optimized4896768080.00$16.0000
r5a.largeMemory optimized121601.67$0.3333
r5a.xlargeMemory optimized243203.33$0.6667
r5a.2xlargeMemory optimized486406.67$1.3333
r5a.4xlargeMemory optimized816128013.33$2.6667
r5a.8xlargeMemory optimized1632256026.67$5.3333
r5a.12xlargeMemory optimized2448384040.00$8.0000
r5a.16xlargeMemory optimized3264512053.33$10.6667
r5a.24xlargeMemory optimized4896768080.00$16.0000
r6a.xlargeMemory optimized243203.33$0.6667
r6a.2xlargeMemory optimized486406.67$1.3333
r6a.4xlargeMemory optimized816128013.33$2.6667
r6a.8xlargeMemory optimized1632256026.67$5.3333
r6a.12xlargeMemory optimized2448384040.00$8.0000
r6a.16xlargeMemory optimized3264512053.33$10.6667
r6a.24xlargeMemory optimized4896768080.00$16.0000
r6a.32xlargeMemory optimized6412810240106.67$21.3333
r6a.48xlargeMemory optimized9619215360160.00$32.0000
r6i.xlargeMemory optimized243203.33$0.6667
r6i.2xlargeMemory optimized486406.67$1.3333
r6i.4xlargeMemory optimized816128013.33$2.6667
r6i.8xlargeMemory optimized1632256026.67$5.3333
r6i.12xlargeMemory optimized2448384040.00$8.0000
r6i.16xlargeMemory optimized3264512053.33$10.6667
r6i.24xlargeMemory optimized4896768080.00$16.0000
r6i.32xlargeMemory optimized6412810240106.67$21.3333
r6id.xlargeMemory optimized243203.33$0.6667
r6id.2xlargeMemory optimized486406.67$1.3333
r6id.4xlargeMemory optimized816128013.33$2.6667
r6id.8xlargeMemory optimized1632256026.67$5.3333
r6id.12xlargeMemory optimized2448384040.00$8.0000
r6id.16xlargeMemory optimized3264512053.33$10.6667
r6id.24xlargeMemory optimized4896768080.00$16.0000
r6id.32xlargeMemory optimized6412810240106.67$21.3333
z1d.largeMemory optimized121601.67$0.3333
z1d.xlargeMemory optimized243203.33$0.6667
z1d.2xlargeMemory optimized486406.67$1.3333
z1d.3xlargeMemory optimized61296010.00$2.0000
z1d.6xlargeMemory optimized1224192020.00$4.0000
z1d.12xlargeMemory optimized2448384040.00$8.0000
        
c4.2xlargeCompute optimized481502.58$0.5167
c4.4xlargeCompute optimized8163005.17$1.0333
c4.8xlargeCompute optimized183660011.00$2.2000
c5.xlargeCompute optimized24801.33$0.2667
c5.2xlargeCompute optimized481602.67$0.5333
c5.4xlargeCompute optimized8163205.33$1.0667
c5.9xlargeCompute optimized183672012.00$2.4000
c5.18xlargeCompute optimized3672144024.00$4.8000
c5d.xlargeCompute optimized24801.33$0.2667
c5d.2xlargeCompute optimized481602.67$0.5333
c5d.4xlargeCompute optimized8163205.33$1.0667
c5d.9xlargeCompute optimized183672012.00$2.4000
c5d.18xlargeCompute optimized3672144024.00$4.8000
c6a.xlargeCompute optimized24801.33$0.2667
c6a.2xlargeCompute optimized481602.67$0.5333
c6a.4xlargeCompute optimized8163205.33$1.0667
c6a.8xlargeCompute optimized163264010.67$2.1333
c6a.12xlargeCompute optimized244896016.00$3.2000
c6a.16xlargeCompute optimized3264128021.33$4.2667
c6a.24xlargeCompute optimized4896192032.00$6.4000
c6a.32xlargeCompute optimized64128256042.67$8.5333
c6a.48xlargeCompute optimized96192384064.00$12.8000
c6i.xlargeCompute optimized24801.33$0.2667
c6i.2xlargeCompute optimized481602.67$0.5333
c6i.4xlargeCompute optimized8163205.33$1.0667
c6i.8xlargeCompute optimized163264010.67$2.1333
c6i.12xlargeCompute optimized244896016.00$3.2000
c6i.16xlargeCompute optimized3264128021.33$4.2667
c6i.24xlargeCompute optimized4896192032.00$6.4000
c6i.32xlargeCompute optimized64128256042.67$8.5333
c6id.xlargeCompute optimized24801.33$0.2667
c6id.2xlargeCompute optimized481602.67$0.5333
c6id.4xlargeCompute optimized8163205.33$1.0667
c6id.8xlargeCompute optimized163264010.67$2.1333
c6id.12xlargeCompute optimized244896016.00$3.2000
c6id.16xlargeCompute optimized3264128021.33$4.2667
c6id.24xlargeCompute optimized4896192032.00$6.4000
c6id.32xlargeCompute optimized64128256042.67$8.5333
        
        
i3.xlargeStorage optimized243103.25$0.6500
i3.2xlargeStorage optimized486106.42$1.2833
i3.4xlargeStorage optimized816122012.83$2.5667
i3.8xlargeStorage optimized1632244025.67$5.1333
i3.16xlargeStorage optimized3264488051.33$10.2667
i2.xlargeStorage optimized243103.25$0.6500
i2.2xlargeStorage optimized486106.42$1.2833
i2.4xlargeStorage optimized816122012.83$2.5667
i2.8xlargeStorage optimized1632244025.67$5.1333
        
p3.2xlargeGPU optimized486116.42$1.8358
p3.8xlargeGPU optimized1632244425.67$7.3433
p3.16xlargeGPU optimized3264488851.33$14.6867
p3dn.24xlargeGPU Optimized4896768880.00$18.7000
p4d.24xlargeGPU Optimized489611528112.00$25.0400
p4de.24xlargeGPU optimized489611528165.33$33.0667
p5.48xlargeGPU optimized9619220488256.00$51.2000
g4dn.xlargeGPU Optimized241612.00$0.5200
g4dn.2xlargeGPU Optimized483214.00$0.8000
g4dn.4xlargeGPU Optimized8166418.00$1.3600
g4dn.8xlargeGPU Optimized1632128116.00$2.4800
g4dn.12xlargeGPU Optimized2448192424.00$4.3200
g4dn.16xlargeGPU Optimized3264256132.00$4.7200
g4dn.metalGPU Optimized4896384848.00$8.6400
g5.xlargeGPU optimized241614.00$0.8000
g5.2xlargeGPU optimized483216.00$1.2000
g5.4xlargeGPU optimized81664110.00$1.4000
g5.8xlargeGPU optimized1632128118.00$2.5200
g5.12xlargeGPU optimized2448192432.00$4.4800
g5.16xlargeGPU optimized3264256134.00$4.7600
g5.24xlargeGPU optimized4896384456.00$7.8400
g5.48xlargeGPU optimized961927688112.00$15.6800

Data Hub - AWS instances

 InstanceCategoryCoresvCPUsRAMGPUCCUsData Hub Rate/hr
m5.xlargeGeneral purpose241602.00$0.0800
m5.2xlargeGeneral purpose483204.00$0.1600
m5.4xlargeGeneral purpose8166408.00$0.3200
m5.8xlargeGeneral purpose1632128016.00$0.6400
m5.12xlargeGeneral purpose2448192024.00$0.9600
m5.16xlargeGeneral purpose3264256032.00$1.0000
m5.24xlargeGeneral purpose4896384048.00$1.0000
m5d.xlargeGeneral purpose241602.00$0.0800
m5d.2xlargeGeneral purpose483204.00$0.1600
m5d.4xlargeGeneral purpose8166408.00$0.3200
m5d.8xlargeGeneral purpose1632128016.00$0.6400
m5d.12xlargeGeneral purpose2448192024.00$0.9600
m5d.16xlargeGeneral purpose3264256032.00$1.0000
m5d.24xlargeGeneral purpose4896384048.00$1.0000
m5n.2xlargeGeneral purpose483204.00$0.1600
m5n.4xlargeGeneral purpose8166408.00$0.3200
m5n.8xlargeGeneral purpose1632128016.00$0.6400
m5dn.xlargeGeneral purpose241602.00$0.0800
m5dn.2xlargeGeneral purpose483204.00$0.1600
m5dn.4xlargeGeneral purpose8166408.00$0.3200
m5dn.8xlargeGeneral purpose1632128016.00$0.6400
m5dn.12xlargeGeneral purpose2448192024.00$0.9600
m5dn.16xlargeGeneral purpose3264256032.00$1.0000
m5dn.24xlargeGeneral purpose4896384048.00$1.0000
m5a.xlargeGeneral purpose241602.00$0.0800
m5a.2xlargeGeneral purpose483204.00$0.1600
m5a.4xlargeGeneral purpose8166408.00$0.3200
m5a.8xlargeGeneral purpose1632128016.00$0.6400
m5a.12xlargeGeneral purpose2448192024.00$0.9600
m5a.16xlargeGeneral purpose3264256032.00$1.0000
m5a.24xlargeGeneral purpose4896384048.00$1.0000
m5ad.xlargeGeneral purpose241602.00$0.0800
m5ad.2xlargeGeneral purpose483204.00$0.1600
m5ad.4xlargeGeneral purpose8166408.00$0.3200
m5ad.8xlargeGeneral purpose1632128016.00$0.6400
m5ad.12xlargeGeneral purpose2448192024.00$0.9600
m5ad.16xlargeGeneral purpose3264256032.00$1.0000
m5ad.24xlargeGeneral purpose4896384048.00$1.0000
m6i.xlargeGeneral purpose241602.00$0.0800
m6i.2xlargeGeneral purpose483204.00$0.1600
m6i.4xlargeGeneral purpose8166408.00$0.3200
m6i.8xlargeGeneral purpose1632128016.00$0.6400
m6i.12xlargeGeneral purpose2448192024.00$0.9600
m6i.16xlargeGeneral purpose3264256032.00$1.0000
m6i.24xlargeGeneral purpose4896384048.00$1.0000
m6i.32xlargeGeneral purpose64128512064.00$1.9200
m6id.xlargeGeneral purpose241602.00$0.0800
m6id.2xlargeGeneral purpose483204.00$0.1600
m6id.4xlargeGeneral purpose8166408.00$0.3200
m6id.8xlargeGeneral purpose1632128016.00$0.6400
m6id.12xlargeGeneral purpose2448192024.00$0.9600
m6id.16xlargeGeneral purpose3264256032.00$1.0000
m6id.24xlargeGeneral purpose4896384048.00$1.0000
m6id.32xlargeGeneral purpose64128512064.00$1.9200
m6a.xlargeGeneral purpose241602.00$0.0800
m6a.2xlargeGeneral purpose483204.00$0.1600
m6a.4xlargeGeneral purpose8166408.00$0.3200
m6a.8xlargeGeneral purpose1632128016.00$0.6400
m6a.12xlargeGeneral purpose2448192024.00$0.9600
m6a.16xlargeGeneral purpose3264256032.00$1.0000
m6a.24xlargeGeneral purpose4896384048.00$1.0000
m6a.32xlargeGeneral purpose64128512064.00$1.9200
m6a.48xlargeGeneral purpose96192768096.00$2.8800
m6in.xlargeGeneral purpose24160.002.00$0.0800
m6in.2xlargeGeneral purpose48320.004.00$0.1600
m6in.4xlargeGeneral purpose816640.008.00$0.3200
m6in.8xlargeGeneral purpose16321280.0016.00$0.6400
m6in.12xlargeGeneral purpose24481920.0024.00$0.9600
m6in.16xlargeGeneral purpose32642560.0032.00$1.2800
m6in.24xlargeGeneral purpose48963840.0048.00$1.9200
m6in.32xlargeGeneral purpose641285120.0064.00$2.5600
m6idn.xlargeGeneral purpose24160.002.00$0.0800
m6idn.2xlargeGeneral purpose48320.004.00$0.1600
m6idn.4xlargeGeneral purpose816640.008.00$0.3200
m6idn.8xlargeGeneral purpose16321280.0016.00$0.6400
m6idn.12xlargeGeneral purpose24481920.0024.00$0.9600
m6idn.16xlargeGeneral purpose32642560.0032.00$1.2800
m6idn.24xlargeGeneral purpose48963840.0048.00$1.9200
m6idn.32xlargeGeneral purpose641285120.0064.00$2.5600
m7i.xlargeGeneral purpose24160.002.00$0.0800
m7i.2xlargeGeneral purpose48320.004.00$0.1600
m7i.4xlargeGeneral purpose816640.008.00$0.3200
m7i.8xlargeGeneral purpose16321280.0016.00$0.6400
m7i.12xlargeGeneral purpose24481920.0024.00$0.9600
m7i.16xlargeGeneral purpose32642560.0032.00$1.2800
m7i.24xlargeGeneral purpose48963840.0048.00$1.9200
m7i.48xlargeGeneral purpose961927680.0096.00$3.8400
m7i-flex.xlargeGeneral purpose24160.002.00$0.0800
m7i-flex.2xlargeGeneral purpose48320.004.00$0.1600
m7i-flex.4xlargeGeneral purpose816640.008.00$0.3200
m7i-flex.8xlargeGeneral purpose16321280.0016.00$0.6400
m7a.xlargeGeneral purpose24160.002.00$0.0800
m7a.2xlargeGeneral purpose48320.004.00$0.1600
m7a.4xlargeGeneral purpose816640.008.00$0.3200
m7a.8xlargeGeneral purpose16321280.0016.00$0.6400
m7a.12xlargeGeneral purpose24481920.0024.00$0.9600
m7a.16xlargeGeneral purpose32642560.0032.00$1.2800
m7a.24xlargeGeneral purpose48963840.0048.00$1.9200
m7a.32xlargeGeneral purpose641285120.0064.00$2.5600
m7a.48xlargeGeneral purpose961927680.0096.00$3.8400
        
r5.2xlargeMemory optimized486406.67$0.2667
r5.4xlargeMemory optimized816128013.33$0.5333
r5.8xlargeMemory optimized1632256026.67$1.0000
r5.16xlargeMemory optimized3264512053.33$1.0000
r5n.2xlargeMemory optimized486406.67$0.2667
r5n.4xlargeMemory optimized816128013.33$0.5333
r5n.8xlargeMemory optimized1632256026.67$1.0000
r5n.16xlargeMemory optimized3264512053.33$1.0000
r5d.xlargeMemory optimized243203.33$0.1333
r5d.2xlargeMemory optimized486406.67$0.2667
r5d.4xlargeMemory optimized816128013.33$0.5333
r5d.8xlargeMemory optimized1632256026.67$1.0000
r5d.12xlargeMemory optimized2448384040.00$1.0000
r5d.16xlargeMemory optimized3264512053.33$1.0000
r5d.24xlargeMemory optimized4896768080.00$2.4000
r5dn.xlargeMemory optimized243203.33$0.1333
r5dn.2xlargeMemory optimized486406.67$0.2667
r5dn.4xlargeMemory optimized816128013.33$0.5333
r5dn.8xlargeMemory optimized1632256026.67$1.0000
r5dn.16xlargeMemory optimized3264512053.33$1.0000
r5a.2xlargeMemory optimized486406.67$0.2667
r5a.4xlargeMemory optimized816128013.33$0.5333
r5a.8xlargeMemory optimized1632256026.67$1.0000
r5ad.xlargeMemory optimized243203.33$0.1333
r5ad.2xlargeMemory optimized486406.67$0.2667
r5ad.4xlargeMemory optimized816128013.33$0.5333
r5ad.8xlargeMemory optimized1632256026.67$1.0000
r5ad.12xlargeMemory optimized2448384040.00$1.0000
r5ad.16xlargeMemory optimized3264512053.33$1.0000
r5ad.24xlargeMemory optimized4896768080.00$2.4000
r4.xlargeMemory optimized2430.503.21$0.1283
r4.2xlargeMemory optimized486106.42$0.2567
r4.4xlargeMemory optimized816122012.83$0.5133
r4.8xlargeMemory optimized1632244025.67$1.0000
x1e.2xlargeMemory optimized48244021.67$0.8667
r6a.xlargeMemory optimized24320.003.33$0.1333
r6a.2xlargeMemory optimized48640.006.67$0.2667
r6a.4xlargeMemory optimized8161280.0013.33$0.5333
r6a.8xlargeMemory optimized16322560.0026.67$1.0667
r6a.12xlargeMemory optimized24483840.0040.00$1.6000
r6a.16xlargeMemory optimized32645120.0053.33$2.1333
r6a.24xlargeMemory optimized48967680.0080.00$3.2000
r6a.32xlargeMemory optimized6412810240.00106.67$4.2667
r6i.xlargeMemory optimized24320.003.33$0.1333
r6i.2xlargeMemory optimized48640.006.67$0.2667
r6i.4xlargeMemory optimized8161280.0013.33$0.5333
r6i.8xlargeMemory optimized16322560.0026.67$1.0667
r6i.12xlargeMemory optimized24483840.0040.00$1.6000
r6i.16xlargeMemory optimized32645120.0053.33$2.1333
r6i.24xlargeMemory optimized48967680.0080.00$3.2000
r6i.32xlargeMemory optimized641281,0240.00106.67$4.2667
r6id.xlargeMemory optimized24320.003.33$0.1333
r6id.2xlargeMemory optimized48640.006.67$0.2667
r6id.4xlargeMemory optimized8161280.0013.33$0.5333
r6id.8xlargeMemory optimized16322560.0026.67$1.0667
r6id.12xlargeMemory optimized24483840.0040.00$1.6000
r6id.16xlargeMemory optimized32645120.0053.33$2.1333
r6id.24xlargeMemory optimized48967680.0080.00$3.2000
r6id.32xlargeMemory optimized641281,0240.00106.67$4.2667
r6in.xlargeMemory optimized24320.003.33$0.1333
r6in.2xlargeMemory optimized48640.006.67$0.2667
r6in.4xlargeMemory optimized8161280.0013.33$0.5333
r6in.8xlargeMemory optimized16322560.0026.67$1.0667
r6in.12xlargeMemory optimized24483840.0040.00$1.6000
r6in.16xlargeMemory optimized32645120.0053.33$2.1333
r6in.24xlargeMemory optimized48967680.0080.00$3.2000
r6in.32xlargeMemory optimized641281,0240.00106.67$4.2667
r6idn.xlargeMemory optimized24320.003.33$0.1333
r6idn.2xlargeMemory optimized48640.006.67$0.2667
r6idn.4xlargeMemory optimized8161280.0013.33$0.5333
r6idn.8xlargeMemory optimized16322560.0026.67$1.0667
r6idn.12xlargeMemory optimized24483840.0040.00$1.6000
r6idn.16xlargeMemory optimized32645120.0053.33$2.1333
r6idn.24xlargeMemory optimized48967680.0080.00$3.2000
r6idn.32xlargeMemory optimized641281,0240.00106.67$4.2667
r7a.xlargeMemory optimized24320.003.33$0.1333
r7a.2xlargeMemory optimized48640.006.67$0.2667
r7a.4xlargeMemory optimized8161280.0013.33$0.5333
r7a.8xlargeMemory optimized16322560.0026.67$1.0667
r7a.12xlargeMemory optimized24483840.0040.00$1.6000
r7a.16xlargeMemory optimized32645120.0053.33$2.1333
r7a.24xlargeMemory optimized48967680.0080.00$3.2000
r7a.32xlargeMemory optimized6412810240.00106.67$4.2667
r7a.48xlargeMemory optimized9619215360.00160.00$6.4000
r7i.xlargeMemory optimized24320.003.33$0.1333
r7i.2xlargeMemory optimized48640.006.67$0.2667
r7i.4xlargeMemory optimized8161280.0013.33$0.5333
r7i.8xlargeMemory optimized16322560.0026.67$1.0667
r7i.12xlargeMemory optimized24483840.0040.00$1.6000
r7i.16xlargeMemory optimized32645120.0053.33$2.1333
r7i.24xlargeMemory optimized48967680.0080.00$3.2000
r7i.48xlargeMemory optimized961921,5360.00160.00$6.4000
r7iz.xlargeMemory optimized24320.003.33$0.1333
r7iz.2xlargeMemory optimized48640.006.67$0.2667
r7iz.4xlargeMemory optimized8161280.0013.33$0.5333
r7iz.8xlargeMemory optimized16322560.0026.67$1.0667
r7iz.12xlargeMemory optimized24483840.0040.00$1.6000
r7iz.16xlargeMemory optimized32645120.0053.33$2.1333
r7iz.32xlargeMemory optimized641281,0240.00106.67$4.2667
        
c5.2xlargeCompute optimized481602.67$0.1067
c5.4xlargeCompute optimized8163205.33$0.2133
c5.9xlargeCompute optimized183672012.00$0.4800
c5.12xlargeCompute optimized244896016.00$0.6400
c5a.2xlargeCompute optimized481602.67$0.1067
c5a.4xlargeCompute optimized8163205.33$0.2133
c5a.8xlargeCompute optimized163264010.67$0.4267
c5a.12xlargeCompute optimized244896016.00$0.6400
c6i.2xlargeCompute optimized48160.002.67$0.1067
c6i.4xlargeCompute optimized816320.005.33$0.2133
c6i.8xlargeCompute optimized1632640.0010.67$0.4267
c6i.12xlargeCompute optimized2448960.0016.00$0.6400
c6i.16xlargeCompute optimized32641280.0021.33$0.8533
c6i.24xlargeCompute optimized48961920.0032.00$1.2800
c6i.32xlargeCompute optimized641282560.0042.67$1.7067
c6id.2xlargeCompute optimized48160.002.67$0.1067
c6id.4xlargeCompute optimized816320.005.33$0.2133
c6id.8xlargeCompute optimized1632640.0010.67$0.4267
c6id.12xlargeCompute optimized2448960.0016.00$0.6400
c6id.16xlargeCompute optimized32641280.0021.33$0.8533
c6id.24xlargeCompute optimized48961920.0032.00$1.2800
c6id.32xlargeCompute optimized641282560.0042.67$1.7067
c6in.2xlargeCompute optimized48160.002.67$0.1067
c6in.4xlargeCompute optimized816320.005.33$0.2133
c6in.8xlargeCompute optimized1632640.0010.67$0.4267
c6in.12xlargeCompute optimized2448960.0016.00$0.6400
c6in.16xlargeCompute optimized32641280.0021.33$0.8533
c6in.24xlargeCompute optimized48961920.0032.00$1.2800
c6in.32xlargeCompute optimized641282560.0042.67$1.7067
c6a.2xlargeCompute optimized48160.002.67$0.1067
c6a.4xlargeCompute optimized816320.005.33$0.2133
c6a.8xlargeCompute optimized1632640.0010.67$0.4267
c6a.12xlargeCompute optimized2448960.0016.00$0.6400
c6a.16xlargeCompute optimized32641280.0021.33$0.8533
c6a.24xlargeCompute optimized48961920.0032.00$1.2800
c6a.32xlargeCompute optimized641282560.0042.67$1.7067
c6a.48xlargeCompute optimized961923840.0064.00$2.5600
c7i.2xlargeCompute optimized48160.002.67$0.1067
c7i.4xlargeCompute optimized816320.005.33$0.2133
c7i.8xlargeCompute optimized1632640.0010.67$0.4267
c7i.12xlargeCompute optimized2448960.0016.00$0.6400
c7i.16xlargeCompute optimized32641280.0021.33$0.8533
c7i.24xlargeCompute optimized48961920.0032.00$1.2800
c7i.48xlargeCompute optimized961923840.0064.00$2.5600
c7a.2xlargeCompute optimized48160.002.67$0.1067
c7a.4xlargeCompute optimized816320.005.33$0.2133
c7a.8xlargeCompute optimized1632640.0010.67$0.4267
c7a.12xlargeCompute optimized2448960.0016.00$0.6400
c7a.16xlargeCompute optimized32641280.0021.33$0.8533
c7a.24xlargeCompute optimized48961920.0032.00$1.2800
c7a.32xlargeCompute optimized641282560.0042.67$1.7067
c7a.48xlargeCompute optimized961923840.0064.00$2.5600
        
i3.2xlargeStorage optimized486106.42$0.2567
i3.4xlargeStorage optimized816122012.83$0.5133
i3.8xlargeStorage optimized1632244025.67$1.0000
i3en.2xlargeStorage optimized486406.67$0.2667
i3en.3xlargeStorage optimized61296010.00$0.4000
i3en.6xlargeStorage optimized1224192020.00$0.8000
i3en.12xlargeStorage optimized2448384040.00$1.0000
i4i.xlargeStorage optimized243203.33$0.1333
i4i.2xlargeStorage optimized486406.67$0.2667
i4i.4xlargeStorage optimized816128013.33$0.5333
i4i.8xlargeStorage optimized1632256026.67$1.0667
i4i.12xlargeStorage optimized2448384040.00$1.6000
i4i.16xlargeStorage optimized3264512053.33$2.1333
i4i.24xlargeStorage optimized4896768080.00$3.2000
i4i.32xlargeStorage optimized641281,0240106.67$4.2667
h1.2xlargeStorage optimized483204.00$0.1600
h1.4xlargeStorage optimized8166408.00$0.3200
h1.8xlargeStorage optimized1632128016.00$0.6400
d2.xlargeStorage optimized2430.503.21$0.1283
d2.2xlargeStorage optimized486106.42$0.2567
d2.4xlargeStorage optimized816122012.83$0.5133
d2.8xlargeStorage optimized1836244026.33$1.0000
d3.xlargeStorage optimized243203.33$0.1333
d3.2xlargeStorage optimized486406.67$0.2667
d3.4xlargeStorage optimized816128013.33$0.5333
d3.8xlargeStorage optimized1632256026.67$1.0000
d3en.2xlargeStorage optimized483204.00$0.1600
d3en.4xlargeStorage optimized8166408.00$0.3200
d3en.6xlargeStorage optimized122496012.00$0.4800
d3en.8xlargeStorage optimized1632128016.00$0.6400
        
p3.2xlargeGPU optimized486116.42$1.1942
p3.8xlargeGPU optimized1632244425.67$4.7500

Data Hub - Flow Management - AWS instances

 

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr*
m5.xlarge General purpose 2 4 16 0 2.00 $0.3000
m5.2xlarge General purpose 4 8 32 0 4.00 $0.6000
m5.4xlarge General purpose 8 16 64 0 8.00 $1.2000
m5.8xlarge General purpose 16 32 128 0 16.00 $2.4000
m5.12xlarge General purpose 24 48 192 0 24.00 $3.6000
m5.16xlarge General purpose 32 64 256 0 32.00 $4.8000
m5.24xlarge General purpose 48 96 384 0 48.00 $7.2000
m5d.xlarge General purpose 2 4 16 0 2.00 $0.3000
m5d.2xlarge General purpose 4 8 32 0 4.00 $0.6000
m5d.4xlarge General purpose 8 16 64 0 8.00 $1.2000
m5d.8xlarge General purpose 16 32 128 0 16.00 $2.4000
m5d.12xlarge General purpose 24 48 192 0 24.00 $3.6000
m5d.16xlarge General purpose 32 64 256 0 32.00 $4.8000
m5d.24xlarge General purpose 48 96 384 0 48.00 $7.2000
m5n.2xlarge General purpose 4 8 32 0 4.00 $0.6000
m5n.4xlarge General purpose 8 16 64 0 8.00 $1.2000
m5n.8xlarge General purpose 16 32 128 0 16.00 $2.4000
m5dn.xlarge General purpose 2 4 16 0 2.00 $0.3000
m5dn.2xlarge General purpose 4 8 32 0 4.00 $0.6000
m5dn.4xlarge General purpose 8 16 64 0 8.00 $1.2000
m5dn.8xlarge General purpose 16 32 128 0 16.00 $2.4000
m5dn.12xlarge General purpose 24 48 192 0 24.00 $3.6000
m5dn.16xlarge General purpose 32 64 256 0 32.00 $4.8000
m5dn.24xlarge General purpose 48 96 384 0 48.00 $7.2000
m5a.xlarge General purpose 2 4 16 0 2.00 $0.3000
m5a.2xlarge General purpose 4 8 32 0 4.00 $0.6000
m5a.4xlarge General purpose 8 16 64 0 8.00 $1.2000
m5a.8xlarge General purpose 16 32 128 0 16.00 $2.4000
m5a.12xlarge General purpose 24 48 192 0 24.00 $3.6000
m5a.16xlarge General purpose 32 64 256 0 32.00 $4.8000
m5a.24xlarge General purpose 48 96 384 0 48.00 $7.2000
m5ad.xlarge General purpose 2 4 16 0 2.00 $0.3000
m5ad.2xlarge General purpose 4 8 32 0 4.00 $0.6000
m5ad.4xlarge General purpose 8 16 64 0 8.00 $1.2000
m5ad.8xlarge General purpose 16 32 128 0 16.00 $2.4000
m5ad.12xlarge General purpose 24 48 192 0 24.00 $3.6000
m5ad.16xlarge General purpose 32 64 256 0 32.00 $4.8000
m5ad.24xlarge General purpose 48 96 384 0 48.00 $7.2000
m6i.xlarge General purpose 2 4 16 0 2.00 $0.3000
m6i.2xlarge General purpose 4 8 32 0 4.00 $0.6000
m6i.4xlarge General purpose 8 16 64 0 8.00 $1.2000
m6i.8xlarge General purpose 16 32 128 0 16.00 $2.4000
m6i.12xlarge General purpose 24 48 192 0 24.00 $3.6000
m6i.16xlarge General purpose 32 64 256 0 32.00 $4.8000
m6i.24xlarge General purpose 48 96 384 0 48.00 $7.2000
m6i.32xlarge General purpose 64 128 512 0 64.00 $9.6000
m6id.xlarge General purpose 2 4 16 0 2.00 $0.3000
m6id.2xlarge General purpose 4 8 32 0 4.00 $0.6000
m6id.4xlarge General purpose 8 16 64 0 8.00 $1.2000
m6id.8xlarge General purpose 16 32 128 0 16.00 $2.4000
m6id.12xlarge General purpose 24 48 192 0 24.00 $3.6000
m6id.16xlarge General purpose 32 64 256 0 32.00 $4.8000
m6id.24xlarge General purpose 48 96 384 0 48.00 $7.2000
m6id.32xlarge General purpose 64 128 512 0 64.00 $9.6000
m6a.xlarge General purpose 2 4 16 0 2.00 $0.3000
m6a.2xlarge General purpose 4 8 32 0 4.00 $0.6000
m6a.4xlarge General purpose 8 16 64 0 8.00 $1.2000
m6a.8xlarge General purpose 16 32 128 0 16.00 $2.4000
m6a.12xlarge General purpose 24 48 192 0 24.00 $3.6000
m6a.16xlarge General purpose 32 64 256 0 32.00 $4.8000
m6a.24xlarge General purpose 48 96 384 0 48.00 $7.2000
m6a.32xlarge General purpose 64 128 512 0 64.00 $9.6000
m6a.48xlarge General purpose 96 192 768 0 96.00 $14.4000
m6in.xlarge General purpose 2 4 16 0.00 2.00 $0.3000
m6in.2xlarge General purpose 4 8 32 0.00 4.00 $0.6000
m6in.4xlarge General purpose 8 16 64 0.00 8.00 $1.2000
m6in.8xlarge General purpose 16 32 128 0.00 16.00 $2.4000
m6in.12xlarge General purpose 24 48 192 0.00 24.00 $3.6000
m6in.16xlarge General purpose 32 64 256 0.00 32.00 $4.8000
m6in.24xlarge General purpose 48 96 384 0.00 48.00 $7.2000
m6in.32xlarge General purpose 64 128 512 0.00 64.00 $9.6000
m6idn.xlarge General purpose 2 4 16 0.00 2.00 $0.3000
m6idn.2xlarge General purpose 4 8 32 0.00 4.00 $0.6000
m6idn.4xlarge General purpose 8 16 64 0.00 8.00 $1.2000
m6idn.8xlarge General purpose 16 32 128 0.00 16.00 $2.4000
m6idn.12xlarge General purpose 24 48 192 0.00 24.00 $3.6000
m6idn.16xlarge General purpose 32 64 256 0.00 32.00 $4.8000
m6idn.24xlarge General purpose 48 96 384 0.00 48.00 $7.2000
m6idn.32xlarge General purpose 64 128 512 0.00 64.00 $9.6000
m7i.xlarge General purpose 2 4 16 0.00 2.00 $0.3000
m7i.2xlarge General purpose 4 8 32 0.00 4.00 $0.6000
m7i.4xlarge General purpose 8 16 64 0.00 8.00 $1.2000
m7i.8xlarge General purpose 16 32 128 0.00 16.00 $2.4000
m7i.12xlarge General purpose 24 48 192 0.00 24.00 $3.6000
m7i.16xlarge General purpose 32 64 256 0.00 32.00 $4.8000
m7i.24xlarge General purpose 48 96 384 0.00 48.00 $7.2000
m7i.48xlarge General purpose 96 192 768 0.00 96.00 $14.4000
m7i-flex.xlarge General purpose 2 4 16 0.00 2.00 $0.3000
m7i-flex.2xlarge General purpose 4 8 32 0.00 4.00 $0.6000
m7i-flex.4xlarge General purpose 8 16 64 0.00 8.00 $1.2000
m7i-flex.8xlarge General purpose 16 32 128 0.00 16.00 $2.4000
m7a.xlarge General purpose 2 4 16 0.00 2.00 $0.3000
m7a.2xlarge General purpose 4 8 32 0.00 4.00 $0.6000
m7a.4xlarge General purpose 8 16 64 0.00 8.00 $1.2000
m7a.8xlarge General purpose 16 32 128 0.00 16.00 $2.4000
m7a.12xlarge General purpose 24 48 192 0.00 24.00 $3.6000
m7a.16xlarge General purpose 32 64 256 0.00 32.00 $4.8000
m7a.24xlarge General purpose 48 96 384 0.00 48.00 $7.2000
m7a.32xlarge General purpose 64 128 512 0.00 64.00 $9.6000
m7a.48xlarge General purpose 96 192 768 0.00 96.00 $14.4000
               
r5.2xlarge Memory optimized 4 8 64 0 6.67 $1.0000
r5.4xlarge Memory optimized 8 16 128 0 13.33 $2.0000
r5.8xlarge Memory optimized 16 32 256 0 26.67 $4.0000
r5.16xlarge Memory optimized 32 64 512 0 53.33 $8.0000
r5n.2xlarge Memory optimized 4 8 64 0 6.67 $1.0000
r5n.4xlarge Memory optimized 8 16 128 0 13.33 $2.0000
r5n.8xlarge Memory optimized 16 32 256 0 26.67 $4.0000
r5n.16xlarge Memory optimized 32 64 512 0 53.33 $8.0000
r5d.xlarge Memory optimized 2 4 32 0 3.33 $0.5000
r5d.2xlarge Memory optimized 4 8 64 0 6.67 $1.0000
r5d.4xlarge Memory optimized 8 16 128 0 13.33 $2.0000
r5d.8xlarge Memory optimized 16 32 256 0 26.67 $4.0000
r5d.12xlarge Memory optimized 24 48 384 0 40.00 $6.0000
r5d.16xlarge Memory optimized 32 64 512 0 53.33 $8.0000
r5d.24xlarge Memory optimized 48 96 768 0 80.00 $12.0000
r5dn.xlarge Memory optimized 2 4 32 0 3.33 $0.5000
r5dn.2xlarge Memory optimized 4 8 64 0 6.67 $1.0000
r5dn.4xlarge Memory optimized 8 16 128 0 13.33 $2.0000
r5dn.8xlarge Memory optimized 16 32 256 0 26.67 $4.0000
r5dn.16xlarge Memory optimized 32 64 512 0 53.33 $8.0000
r5a.2xlarge Memory optimized 4 8 64 0 6.67 $1.0000
r5a.4xlarge Memory optimized 8 16 128 0 13.33 $2.0000
r5a.8xlarge Memory optimized 16 32 256 0 26.67 $4.0000
r5ad.xlarge Memory optimized 2 4 32 0 3.33 $0.5000
r5ad.2xlarge Memory optimized 4 8 64 0 6.67 $1.0000
r5ad.4xlarge Memory optimized 8 16 128 0 13.33 $2.0000
r5ad.8xlarge Memory optimized 16 32 256 0 26.67 $4.0000
r5ad.12xlarge Memory optimized 24 48 384 0 40.00 $6.0000
r5ad.16xlarge Memory optimized 32 64 512 0 53.33 $8.0000
r5ad.24xlarge Memory optimized 48 96 768 0 80.00 $12.0000
r4.xlarge Memory optimized 2 4 30.5 0 3.21 $0.4813
r4.2xlarge Memory optimized 4 8 61 0 6.42 $0.9625
r4.4xlarge Memory optimized 8 16 122 0 12.83 $1.9250
r4.8xlarge Memory optimized 16 32 244 0 25.67 $3.8500
x1e.2xlarge Memory optimized 4 8 244 0 21.67 $3.2500
r6a.xlarge Memory optimized 2 4 32 0.00 3.33 $0.5000
r6a.2xlarge Memory optimized 4 8 64 0.00 6.67 $1.0000
r6a.4xlarge Memory optimized 8 16 128 0.00 13.33 $2.0000
r6a.8xlarge Memory optimized 16 32 256 0.00 26.67 $4.0000
r6a.12xlarge Memory optimized 24 48 384 0.00 40.00 $6.0000
r6a.16xlarge Memory optimized 32 64 512 0.00 53.33 $8.0000
r6a.24xlarge Memory optimized 48 96 768 0.00 80.00 $12.0000
r6a.32xlarge Memory optimized 64 128 1024 0.00 106.67 $16.0000
r6i.xlarge Memory optimized 2 4 32 0.00 3.33 $0.5000
r6i.2xlarge Memory optimized 4 8 64 0.00 6.67 $1.0000
r6i.4xlarge Memory optimized 8 16 128 0.00 13.33 $2.0000
r6i.8xlarge Memory optimized 16 32 256 0.00 26.67 $4.0000
r6i.12xlarge Memory optimized 24 48 384 0.00 40.00 $6.0000
r6i.16xlarge Memory optimized 32 64 512 0.00 53.33 $8.0000
r6i.24xlarge Memory optimized 48 96 768 0.00 80.00 $12.0000
r6i.32xlarge Memory optimized 64 128 1,024 0.00 106.67 $16.0000
r6id.xlarge Memory optimized 2 4 32 0.00 3.33 $0.5000
r6id.2xlarge Memory optimized 4 8 64 0.00 6.67 $1.0000
r6id.4xlarge Memory optimized 8 16 128 0.00 13.33 $2.0000
r6id.8xlarge Memory optimized 16 32 256 0.00 26.67 $4.0000
r6id.12xlarge Memory optimized 24 48 384 0.00 40.00 $6.0000
r6id.16xlarge Memory optimized 32 64 512 0.00 53.33 $8.0000
r6id.24xlarge Memory optimized 48 96 768 0.00 80.00 $12.0000
r6id.32xlarge Memory optimized 64 128 1,024 0.00 106.67 $16.0000
r6in.xlarge Memory optimized 2 4 32 0.00 3.33 $0.5000
r6in.2xlarge Memory optimized 4 8 64 0.00 6.67 $1.0000
r6in.4xlarge Memory optimized 8 16 128 0.00 13.33 $2.0000
r6in.8xlarge Memory optimized 16 32 256 0.00 26.67 $4.0000
r6in.12xlarge Memory optimized 24 48 384 0.00 40.00 $6.0000
r6in.16xlarge Memory optimized 32 64 512 0.00 53.33 $8.0000
r6in.24xlarge Memory optimized 48 96 768 0.00 80.00 $12.0000
r6in.32xlarge Memory optimized 64 128 1,024 0.00 106.67 $16.0000
r6idn.xlarge Memory optimized 2 4 32 0.00 3.33 $0.5000
r6idn.2xlarge Memory optimized 4 8 64 0.00 6.67 $1.0000
r6idn.4xlarge Memory optimized 8 16 128 0.00 13.33 $2.0000
r6idn.8xlarge Memory optimized 16 32 256 0.00 26.67 $4.0000
r6idn.12xlarge Memory optimized 24 48 384 0.00 40.00 $6.0000
r6idn.16xlarge Memory optimized 32 64 512 0.00 53.33 $8.0000
r6idn.24xlarge Memory optimized 48 96 768 0.00 80.00 $12.0000
r6idn.32xlarge Memory optimized 64 128 1,024 0.00 106.67 $16.0000
r7a.xlarge Memory optimized 2 4 32 0.00 3.33 $0.5000
r7a.2xlarge Memory optimized 4 8 64 0.00 6.67 $1.0000
r7a.4xlarge Memory optimized 8 16 128 0.00 13.33 $2.0000
r7a.8xlarge Memory optimized 16 32 256 0.00 26.67 $4.0000
r7a.12xlarge Memory optimized 24 48 384 0.00 40.00 $6.0000
r7a.16xlarge Memory optimized 32 64 512 0.00 53.33 $8.0000
r7a.24xlarge Memory optimized 48 96 768 0.00 80.00 $12.0000
r7a.32xlarge Memory optimized 64 128 1024 0.00 106.67 $16.0000
r7a.48xlarge Memory optimized 96 192 1536 0.00 160.00 $24.0000
r7i.xlarge Memory optimized 2 4 32 0.00 3.33 $0.5000
r7i.2xlarge Memory optimized 4 8 64 0.00 6.67 $1.0000
r7i.4xlarge Memory optimized 8 16 128 0.00 13.33 $2.0000
r7i.8xlarge Memory optimized 16 32 256 0.00 26.67 $4.0000
r7i.12xlarge Memory optimized 24 48 384 0.00 40.00 $6.0000
r7i.16xlarge Memory optimized 32 64 512 0.00 53.33 $8.0000
r7i.24xlarge Memory optimized 48 96 768 0.00 80.00 $12.0000
r7i.48xlarge Memory optimized 96 192 1,536 0.00 160.00 $24.0000
r7iz.xlarge Memory optimized 2 4 32 0.00 3.33 $0.5000
r7iz.2xlarge Memory optimized 4 8 64 0.00 6.67 $1.0000
r7iz.4xlarge Memory optimized 8 16 128 0.00 13.33 $2.0000
r7iz.8xlarge Memory optimized 16 32 256 0.00 26.67 $4.0000
r7iz.12xlarge Memory optimized 24 48 384 0.00 40.00 $6.0000
r7iz.16xlarge Memory optimized 32 64 512 0.00 53.33 $8.0000
r7iz.32xlarge Memory optimized 64 128 1,024 0.00 106.67 $16.0000
               
c5.2xlarge Compute optimized 4 8 16 0 2.67 $0.4000
c5.4xlarge Compute optimized 8 16 32 0 5.33 $0.8000
c5.9xlarge Compute optimized 18 36 72 0 12.00 $1.8000
c5.12xlarge Compute optimized 24 48 96 0 16.00 $2.4000
c5a.2xlarge Compute optimized 4 8 16 0 2.67 $0.4000
c5a.4xlarge Compute optimized 8 16 32 0 5.33 $0.8000
c5a.8xlarge Compute optimized 16 32 64 0 10.67 $1.6000
c5a.12xlarge Compute optimized 24 48 96 0 16.00 $2.4000
c6i.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.4000
c6i.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.8000
c6i.8xlarge Compute optimized 16 32 64 0.00 10.67 $1.6000
c6i.12xlarge Compute optimized 24 48 96 0.00 16.00 $2.4000
c6i.16xlarge Compute optimized 32 64 128 0.00 21.33 $3.2000
c6i.24xlarge Compute optimized 48 96 192 0.00 32.00 $4.8000
c6i.32xlarge Compute optimized 64 128 256 0.00 42.67 $6.4000
c6id.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.4000
c6id.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.8000
c6id.8xlarge Compute optimized 16 32 64 0.00 10.67 $1.6000
c6id.12xlarge Compute optimized 24 48 96 0.00 16.00 $2.4000
c6id.16xlarge Compute optimized 32 64 128 0.00 21.33 $3.2000
c6id.24xlarge Compute optimized 48 96 192 0.00 32.00 $4.8000
c6id.32xlarge Compute optimized 64 128 256 0.00 42.67 $6.4000
c6in.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.4000
c6in.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.8000
c6in.8xlarge Compute optimized 16 32 64 0.00 10.67 $1.6000
c6in.12xlarge Compute optimized 24 48 96 0.00 16.00 $2.4000
c6in.16xlarge Compute optimized 32 64 128 0.00 21.33 $3.2000
c6in.24xlarge Compute optimized 48 96 192 0.00 32.00 $4.8000
c6in.32xlarge Compute optimized 64 128 256 0.00 42.67 $6.4000
c6a.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.4000
c6a.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.8000
c6a.8xlarge Compute optimized 16 32 64 0.00 10.67 $1.6000
c6a.12xlarge Compute optimized 24 48 96 0.00 16.00 $2.4000
c6a.16xlarge Compute optimized 32 64 128 0.00 21.33 $3.2000
c6a.24xlarge Compute optimized 48 96 192 0.00 32.00 $4.8000
c6a.32xlarge Compute optimized 64 128 256 0.00 42.67 $6.4000
c6a.48xlarge Compute optimized 96 192 384 0.00 64.00 $9.6000
c7i.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.4000
c7i.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.8000
c7i.8xlarge Compute optimized 16 32 64 0.00 10.67 $1.6000
c7i.12xlarge Compute optimized 24 48 96 0.00 16.00 $2.4000
c7i.16xlarge Compute optimized 32 64 128 0.00 21.33 $3.2000
c7i.24xlarge Compute optimized 48 96 192 0.00 32.00 $4.8000
c7i.48xlarge Compute optimized 96 192 384 0.00 64.00 $9.6000
c7a.2xlarge Compute optimized 4 8 16 0.00 2.67 $0.4000
c7a.4xlarge Compute optimized 8 16 32 0.00 5.33 $0.8000
c7a.8xlarge Compute optimized 16 32 64 0.00 10.67 $1.6000
c7a.12xlarge Compute optimized 24 48 96 0.00 16.00 $2.4000
c7a.16xlarge Compute optimized 32 64 128 0.00 21.33 $3.2000
c7a.24xlarge Compute optimized 48 96 192 0.00 32.00 $4.8000
c7a.32xlarge Compute optimized 64 128 256 0.00 42.67 $6.4000
c7a.48xlarge Compute optimized 96 192 384 0.00 64.00 $9.6000
               
i3.2xlarge Storage optimized 4 8 61 0 6.42 $0.9625
i3.4xlarge Storage optimized 8 16 122 0 12.83 $1.9250
i3.8xlarge Storage optimized 16 32 244 0 25.67 $3.8500
i3en.2xlarge Storage optimized 4 8 64 0 6.67 $1.0000
i3en.3xlarge Storage optimized 6 12 96 0 10.00 $1.5000
i3en.6xlarge Storage optimized 12 24 192 0 20.00 $3.0000
i3en.12xlarge Storage optimized 24 48 384 0 40.00 $6.0000
i4i.xlarge Storage optimized 2 4 32 0 3.33 $0.5000
i4i.2xlarge Storage optimized 4 8 64 0 6.67 $1.0000
i4i.4xlarge Storage optimized 8 16 128 0 13.33 $2.0000
i4i.8xlarge Storage optimized 16 32 256 0 26.67 $4.0000
i4i.12xlarge Storage optimized 24 48 384 0 40.00 $6.0000
i4i.16xlarge Storage optimized 32 64 512 0 53.33 $8.0000
i4i.24xlarge Storage optimized 48 96 768 0 80.00 $12.0000
i4i.32xlarge Storage optimized 64 128 1,024 0 106.67 $16.0000
h1.2xlarge Storage optimized 4 8 32 0 4.00 $0.6000
h1.4xlarge Storage optimized 8 16 64 0 8.00 $1.2000
h1.8xlarge Storage optimized 16 32 128 0 16.00 $2.4000
d2.xlarge Storage optimized 2 4 30.5 0 3.21 $0.4813
d2.2xlarge Storage optimized 4 8 61 0 6.42 $0.9625
d2.4xlarge Storage optimized 8 16 122 0 12.83 $1.9250
d2.8xlarge Storage optimized 18 36 244 0 26.33 $3.9500
d3.xlarge Storage optimized 2 4 32 0 3.33 $0.5000
d3.2xlarge Storage optimized 4 8 64 0 6.67 $1.0000
d3.4xlarge Storage optimized 8 16 128 0 13.33 $2.0000
d3.8xlarge Storage optimized 16 32 256 0 26.67 $4.0000
d3en.2xlarge Storage optimized 4 8 32 0 4.00 $0.6000
d3en.4xlarge Storage optimized 8 16 64 0 8.00 $1.2000
d3en.6xlarge Storage optimized 12 24 96 0 12.00 $1.8000
d3en.8xlarge Storage optimized 16 32 128 0 16.00 $2.4000
               
p3.2xlarge GPU optimized 4 8 61 1 6.42 $0.9625
p3.8xlarge GPU optimized 16 32 244 4 25.67 $3.8500

Operational Database - AWS instances

               
Instance* Category Cores vCPUs RAM GPU CCUs Rate/hr
m5.2xlarge General purpose 4 8 32 0 4.00 $0.3200
m5.4xlarge General purpose 8 16 64 0 8.00 $0.6400
m5.8xlarge General purpose 16 32 128 0 16.00 $1.2800
               
r5.8xlarge Memory optimized 16 32 256 0 26.67 $2.1333
               
c5.12xlarge Compute optimized 24 48 96 0 16 $1.2800
               
h1.2xlarge Storage optimized 4 8 32 0 4.00 $0.3200
i3.2xlarge Storage Optimized 4 8 61 0 6.42 $0.5133

* Instance type is auto-selected by Operational Database based on workload needs

DataFlow Deployments & Test Sessions - AWS instances

Node Type vCPUs Memory GPU CCUs Rate/hr
Extra Small 2 4 0 0.67 $0.2000
Small 3 6 0 1.00 $0.3000
Medium 6 12 0 2.00 $0.6000
Large 12 24 0 4.00 $1.2000
*Note: Test Sessions always use the Extra Small node type

DataFlow Functions - AWS

Total Billable Invocations per Flow/Month Price per Billable Invocation

First 1,000 Billable Invocations

$0.1000

Next 9,000 Billable Invocations

$0.0200

Next 90,000 Billable Invocations

$0.0020

Next 900,000 Billable Invocations

$0.0003

Over 1,000,001 Billable Invocations

$0.0001

*Notes:
  • Pricing Volume Tiers are per individual DataFlow Function
  • The volume table above is a tiered volume table, where the first 1,000 invocations are always charged at $0.10 per month, the next 9,000 invocations per month are charged at $0.02 per month and so on
  • “Billable invocation” is a combination of function invocations and function duration. Every time an instance of DataFlow Functions is invoked that counts as one Billable Invocation. If a DFF runs for more than one second, each subsequent second (after the initial second) counts as another Billable Invocation.  In addition, if a DFF invocation runs for less than one second, each fractional second will count as one Billable Invocation.

Data Engineering - Azure instances

Instance* Category Cores vCPUs RAM GPU CCUs Core Rate/hr All-Purpose Rate/hr
D8s v4 General purpose 4 8 32 0 4 $0.28 $0.8000
D16s v4 General purpose 8 16 64 0 8 $0.5600 $1.6000
D32s v4 General purpose 16 32 128 0 16.00 $1.1200 $3.2000
D64s v4 General purpose 32 64 256 0 32.00 $2.2400 $6.4000
D8as v4 General purpose 4 8 32 0 4.00 $0.2800 $0.8000
D16as v4 General purpose 8 16 64 0 8.00 $0.5600 $1.6000
D32as v4 General purpose 16 32 128 0 16.00 $1.1200 $3.2000
D48as v4 General purpose 24 48 192 0 24.00 $1.6800 $4.8000
D64as v4 General purpose 32 64 256 0 32.00 $2.2400 $6.4000
D4as v5 General purpose 2 4 16 0 2.00 $0.1400 $0.4000
D8as v5 General purpose 4 8 32 0 4.00 $0.2800 $0.8000
D16as v5 General purpose 8 16 64 0 8.00 $0.5600 $1.6000
D32as v5 General purpose 16 32 128 0 16.00 $1.1200 $3.2000
D48as v5 General purpose 24 48 192 0 24.00 $1.6800 $4.8000
D64as v5 General purpose 32 64 256 0 32.00 $2.2400 $6.4000
                 
E8s v3 Memory optimized 4 8 64 0 6.67 $0.4667 $1.3333
E16s v3 Memory optimized 8 16 128 0 13.33 $0.9333 $2.6667
E32s v3 Memory optimized 16 32 256 0 26.67 $1.8667 $5.3333
E64s v3 Memory optimized 32 64 432 0 46.67 $3.2667 $9.3333
E8s v4 Memory optimized 4 8 64 0 6.67 $0.4667 $1.3333
E16s v4 Memory optimized 8 16 128 0 13.33 $0.9333 $2.6667
E32s v4 Memory optimized 16 32 256 0 26.67 $1.8667 $5.3333
E64s v4 Memory optimized 32 64 504 0 52.67 $3.6867 $10.5333
E8as v4 Memory optimized 4 8 64 0 6.67 $0.4667 $1.3333
E16as v4 Memory optimized 8 16 128 0 13.33 $0.9333 $2.6667
E20as v4 Memory optimized 10 20 160 0 16.67 $1.1667 $3.3333
E32as v4 Memory optimized 16 32 256 0 26.67 $1.8667 $5.3333
E48as v4 Memory optimized 24 48 384 0 40.00 $2.8000 $8.0000
E64as v4 Memory optimized 32 64 512 0 53.33 $3.7333 $10.6667
E96as v4 Memory optimized 48 96 672 0 72.00 $5.0400 $14.4000
                 
F8s v2 Compute optimized 4 8 16 0 2.67 $0.1867 $0.5333
F16s v2 Compute optimized 8 16 32 0 5.33 $0.3733 $1.0667
F32s v2 Compute optimized 16 32 64 0 10.67 $0.7467 $2.1333
F48s v2 Compute optimized 24 48 96 0 16.00 $1.1200 $3.2000
F72s v2 Compute optimized 36 72 144 0 24.00 $1.6800 $4.8000
F48s v2 Compute optimized 24 48 96 0 16.00 $1.1200 $12.8000
F72s v2 Compute optimized 36 72 144 0 24.00 $1.6800 $19.2000

 

* Instance type is auto-selected by Operational Database based on workload needs

Data Warehouse - Azure instances

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr
E16 v3 Memory optimized 8 16 128 0 13.33 $0.9333
E16ds v4 Memory-optimized 8 16 128 0 13.33 $0.9333
E16ads v5 Memory optimized 8 16 128 0 13.33 $0.9333
E16ds v5 Memory optimized 8 16 128 0 13.33 $0.9333

Machine Learning - Azure instances

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr
DS3 v2 General purpose 2 4 14 0 1.83 $0.3667
DS4 v2 General purpose 4 8 28 0 3.67 $0.7333
DS5 v2 General purpose 8 16 56 0 7.33 $1.4667
D3 v2 General purpose 2 4 14 0 1.83 $0.3667
D8s v3 General purpose 4 8 32 0 4 $0.8000
D16s v3 General purpose 8 16 64 0 8 $1.6000
D32s v3 General purpose 16 32 128 0 16 $3.2000
D64s v3 General purpose 32 64 256 0 32 $6.4000
D8 v3 General purpose 4 8 32 0 4 $0.8000
D16 v3 General purpose 8 16 64 0 8 $1.6000
D32 v3 General purpose 16 32 128 0 16 $3.2000
D64 v3 General purpose 32 64 256 0 32 $6.4000
DS12 v2 General purpose 2 4 28 0 3 $0.6000
DS13 v2 General purpose 4 8 56 0 6 $1.2000
DS14 v2 General purpose 8 16 112 0 12 $2.4000
DS15 v2 General purpose 10 20 140 0 15 $3.0000
D12 v2 General purpose 2 4 28 0 3 $0.6000
D13 v2 General purpose 4 8 56 0 6 $1.2000
D14 v2 General purpose 8 16 112 0 12 $2.4000
D15 v2 General purpose 10 20 140 0 15 $3.0000
D4as v4 General purpose 2 4 16 0 2 $0.4000
D8as v4 General purpose 4 8 32 0 4 $0.8000
D16as v4 General purpose 8 16 64 0 8 $1.6000
D32as v4 General purpose 16 32 128 0 16 $3.2000
D48as v4 General purpose 24 48 192 0 24 $4.8000
D64as v4 General purpose 32 64 256 0 32 $6.4000
D96as v4 General purpose 48 96 384 0 48 $9.6000
D4as v5 General purpose 2 4 16 0 2 $0.4000
D8as v5 General purpose 4 8 32 0 4 $0.8000
D16as v5 General purpose 8 16 64 0 8 $1.6000
D32as v5 General purpose 16 32 128 0 16 $3.2000
D48as v5 General purpose 24 48 192 0 24 $4.8000
D64as v5 General purpose 32 64 256 0 32 $6.4000
D96as v5 General purpose 48 96 384 0 48 $9.6000
               
E8s v3 Memory optimized 4 8 64 0 6.67 $1.3333
E16s v3 Memory optimized 8 16 128 0 13.33 $2.6667
E32s v3 Memory optimized 16 32 256 0 26.67 $5.3333
E64s v3 Memory optimized 32 64 432 0 46.67 $9.3333
               
L4s Storage optimized 2 4 32 0 3.33 $0.6667
L8s Storage optimized 4 8 64 0 6.67 $1.3333
L16s Storage optimized 8 16 128 0 13.33 $2.6667
L32s Storage optimized 16 32 256 0 26.67 $5.3333
L8s v2 Storage optimized 4 8 64 0 6.67 $1.3333
L16s v2 Storage optimized 8 16 128 0 13.33 $2.6667
L32s v2 Storage optimized 16 32 256 0 26.67 $5.3333
L64s v2 Storage optimized 32 64 512 0 53.33 $10.6667
L80s v2 Storage optimized 40 80 640 0 66.67 $13.3333
F4s v2 Storage optimized 2 4 8 0 1.33 $0.2667
F8s v2 Storage optimized 4 8 16 0 2.67 $0.5333
F16s v2 Storage optimized 8 16 32 0 5.33 $1.0667
F32s v2 Storage optimized 16 32 64 0 10.67 $2.1333
F64s v2 Storage optimized 32 64 128 0 21.33 $4.2667
F72s v2 Storage optimized 36 72 144 0 24 $4.8000
F4 Storage optimized 2 4 8 0 1.33 $0.2667
F8 Storage optimized 4 8 16 0 2.67 $0.5333
F16 Storage optimized 8 16 32 0 5.33 $1.0667
               
H16 High performance 16 32 112 0 14.67 $2.9333
               
NC6 GPU optimized 3 6 56 1 5.67 $0.9246
NC12 GPU optimized 6 12 112 2 11.33 $1.8492
NC24 GPU optimized 12 24 224 4 22.67 $3.6983
NC6s v2 GPU optimized 3 6 112 1 10.33 $1.7467
NC12s v2 GPU optimized 6 12 224 2 20.67 $3.4933
NC24s v2 GPU optimized 12 24 448 4 41.33 $6.9867
NC6s v3 GPU optimized 3 6 112 1 10.33 $2.3842
NC12s v3 GPU optimized 6 12 224 2 20.67 $4.7683
NC24s v3 GPU optimized 12 24 448 4 41.33 $9.5367
NC4as T4 v3 GPU optimized 2 4 28 1 3 $0.6600
NC8as T4 v3 GPU optimized 4 8 56 1 6 $1.0800
NC16as T4 v3 GPU optimized 8 16 110 1 11.83 $1.8967
NC64as T4 v3 GPU optimized 32 64 440 4 47.33 $7.5867
ND6s GPU optimized 6 12 112 1 11.33 $1.9467
ND12s GPU optimized 12 24 224 2 22.67 $3.8933
ND24s GPU optimized 24 48 448 4 45.33 $7.7867
ND96asr A100 v4 GPU optimized 96 192 900 8 107 $24.3400
NV24s v3 GPU optimized 12 24 224 2 22.67 $3.4358
NV12s v3 GPU optimized 6 12 112 1 11.33 $2.2667
NV48s v3 GPU optimized 24 48 448 4 45.33 $9.0667
NV36adms A10 v5 GPU optimized 18 36 880 1 81.33 $16.2667
NV36ads A10 v5 GPU optimized 18 36 440 1 44.67 $8.9333
NV72ads A10 v5 GPU optimized 36 72 880 2 89.33 $17.8667

Data Hub - Azure instances

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr
D5 v2 General purpose 8 16 56 0 7.33 $0.2933
D8 v3 General purpose 4 8 32 0 4.00 $0.1600
D16 v3 General purpose 8 16 64 0 8.00 $0.3200
D32 v3 General purpose 16 32 128 0 16.00 $0.6400
D64 v3 General purpose 32 64 256 0 32.00 $1.0000
D4s v3 General purpose 2 4 16 0 2.00 $0.0800
D8s v3 General purpose 4 8 32 0 4.00 $0.1600
D16s v3 General purpose 8 16 64 0 8.00 $0.3200
D32s v3 General purpose 16 32 128 0 16.00 $0.6400
D48s v3 General purpose 24 48 192 0 24.00 $0.9600
D64s v3 General purpose 32 64 256 0 32.00 $1.0000
D8a v4 General purpose 4 8 32 0 4.00 $0.1600
D16a v4 General purpose 8 16 64 0 8.00 $0.3200
D32a v4 General purpose 16 32 128 0 16.00 $0.6400
D64a v4 General purpose 32 64 256 0 32.00 $1.0000
D8as v4 General purpose 4 8 32 0 4.00 $0.1600
D16as v4 General purpose 8 16 64 0 8.00 $0.3200
D32as v4 General purpose 16 32 128 0 16.00 $0.6400
D64as v4 General purpose 32 64 256 0 32.00 $1.0000
D8 v5 General purpose 4 8 32 0 4.00 $0.1600
D16 v5 General purpose 8 16 64 0 8.00 $0.3200
D32 v5 General purpose 16 32 128 0 16.00 $0.6400
D48 v5 General purpose 24 48 192 0 24.00 $0.9600
D64 v5 General purpose 32 64 256 0 32.00 $1.0000
D8s v5 General purpose 4 8 32 0 4.00 $0.1600
D16s v5 General purpose 8 16 64 0 8.00 $0.3200
D32s v5 General purpose 16 32 128 0 16.00 $0.6400
D48s v5 General purpose 24 48 192 0 24.00 $0.9600
D64s v5 General purpose 32 64 256 0 32.00 $1.0000
D8as v5 General purpose 4 8 32 0 4.00 $0.1600
D16as v5 General purpose 8 16 64 0 8.00 $0.3200
D32as v5 General purpose 16 32 128 0 16.00 $0.6400
D48as v5 General purpose 24 48 192 0 24.00 $0.9600
D64as v5 General purpose 32 64 256 0 32.00 $1.0000
               
D13 v2 Memory optimized 4 8 56 0 6.00 $0.2400
D14 v2 Memory optimized 8 16 112 0 12.00 $0.4800
E4 v3 Memory optimized 2 4 32 0 3.33 $0.1333
E8 v3 Memory optimized 4 8 64 0 6.67 $0.2667
E16 v3 Memory optimized 8 16 128 0 13.33 $0.5333
E32 v3 Memory optimized 16 32 256 0 26.67 $1.0000
E64 v3 Memory optimized 32 64 432 0 46.67 $1.0000
E4s v3 Memory optimized 2 4 32 0 3.33 $0.1333
E8s v3 Memory optimized 4 8 64 0 6.67 $0.2667
E16s v3 Memory optimized 8 16 128 0 13.33 $0.5333
E16-8s v3 Memory optimized 4 8 128 0 12.00 $0.4800
E20s v3 Memory optimized 10 20 160 0 16.67 $0.6667
E32s v3 Memory optimized 16 32 256 0 26.67 $1.0000
E48s v3 Memory optimized 24 48 384 0 40.00 $1.0000
E64s v3 Memory optimized 32 64 432 0 46.67 $1.0000
E8a v4 Memory optimized 4 8 64 0 6.67 $0.2667
E16a v4 Memory optimized 8 16 128 0 13.33 $0.5333
E32a v4 Memory optimized 16 32 256 0 26.67 $1.0000
E64a v4 Memory optimized 32 64 512 0 53.33 $1.0000
E4s v4 Memory optimized 2 4 32 0 3.33 $0.1333
E8s v4 Memory optimized 4 8 64 0 6.67 $0.2667
E16s v4 Memory optimized 8 16 128 0 13.33 $0.5333
E20s v4 Memory optimized 10 20 160 0 16.67 $0.6667
E32s v4 Memory optimized 16 32 256 0 26.67 $1.0000
E48s v4 Memory optimized 24 48 384 0 40.00 $1.0000
E64s v4 Memory optimized 32 64 504 0 52.67 $1.0000
E4ds v4 Memory optimized 2 4 32 0 3.33 $0.1333
E8ds v4 Memory optimized 4 8 64 0 6.67 $0.2667
E16ds v4 Memory optimized 8 16 128 0 13.33 $0.5333
E20ds v4 Memory optimized 10 20 160 0 16.67 $0.6667
E32ds v4 Memory optimized 16 32 256 0 26.67 $1.0000
E48ds v4 Memory optimized 24 48 384 0 40.00 $1.0000
E64ds v4 Memory optimized 32 64 504 0 52.67 $1.0000
E4a v4 Memory optimized 2 4 32 0 3.33 $0.1333
E4as v5 Memory optimized 2 4 32 0 3.33 $0.1333
E8as v5 Memory optimized 4 8 64 0 6.67 $0.2667
E16as v5 Memory optimized 8 16 128 0 13.33 $0.5333
E20as v5 Memory optimized 10 20 160 0 16.67 $0.6667
E32as v5 Memory optimized 16 32 256 0 26.67 $1.0000
E48as v5 Memory optimized 24 48 384 0 40.00 $1.0000
E64as v5 Memory optimized 32 64 512 0 53.33 $1.0000
               
F8s v2 Compute optimized 4 8 16 0 2.67 $0.1067
F16s v2 Compute optimized 8 16 32 0 5.33 $0.2133
F32s v2 Compute optimized 16 32 64 0 10.67 $0.4267
               
L8s v2 Storage optimized 4 8 64 0 6.67 $0.2667
L16s v2 Storage optimized 8 16 128 0 13.33 $0.5333
L32s v2 Storage optimized 16 32 256 0 26.67 $1.0000
L48s v2 Storage optimized 24 48 384 0 40.00 $1.0000
               
NC6 GPU optimized 3 6 56 1 5.67 $0.3579
NC24r GPU optimized 12 24 224 4 22.67 $1.4317
NC6s v3 GPU optimized 3 6 112 1 10.33 $1.3508
NC24s v3 GPU optimized 12 24 448 4 41.33 $4.7500

Data Hub - Flow Management - Azure instances

 

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr*
D5 v2 General purpose 8 16 56 0 7.33 $1.1000
D8 v3 General purpose 4 8 32 0 4.00 $0.6000
D16 v3 General purpose 8 16 64 0 8.00 $1.2000
D32 v3 General purpose 16 32 128 0 16.00 $2.4000
D64 v3 General purpose 32 64 256 0 32.00 $4.8000
D4s v3 General purpose 2 4 16 0 2.00 $0.3000
D8s v3 General purpose 4 8 32 0 4.00 $0.6000
D16s v3 General purpose 8 16 64 0 8.00 $1.2000
D32s v3 General purpose 16 32 128 0 16.00 $2.4000
D48s v3 General purpose 24 48 192 0 24.00 $3.6000
D64s v3 General purpose 32 64 256 0 32.00 $4.8000
D8a v4 General purpose 4 8 32 0 4.00 $0.6000
D16a v4 General purpose 8 16 64 0 8.00 $1.2000
D32a v4 General purpose 16 32 128 0 16.00 $2.4000
D64a v4 General purpose 32 64 256 0 32.00 $4.8000
D8as v4 General purpose 4 8 32 0 4.00 $0.6000
D16as v4 General purpose 8 16 64 0 8.00 $1.2000
D32as v4 General purpose 16 32 128 0 16.00 $2.4000
D64as v4 General purpose 32 64 256 0 32.00 $4.8000
D8 v5 General purpose 4 8 32 0 4.00 $0.6000
D16 v5 General purpose 8 16 64 0 8.00 $1.2000
D32 v5 General purpose 16 32 128 0 16.00 $2.4000
D48 v5 General purpose 24 48 192 0 24.00 $3.6000
D64 v5 General purpose 32 64 256 0 32.00 $4.8000
D8s v5 General purpose 4 8 32 0 4.00 $0.6000
D16s v5 General purpose 8 16 64 0 8.00 $1.2000
D32s v5 General purpose 16 32 128 0 16.00 $2.4000
D48s v5 General purpose 24 48 192 0 24.00 $3.6000
D64s v5 General purpose 32 64 256 0 32.00 $4.8000
D8as v5 General purpose 4 8 32 0 4.00 $0.6000
D16as v5 General purpose 8 16 64 0 8.00 $1.2000
D32as v5 General purpose 16 32 128 0 16.00 $2.4000
D48as v5 General purpose 24 48 192 0 24.00 $3.6000
D64as v5 General purpose 32 64 256 0 32.00 $4.8000
               
D13 v2 Memory optimized 4 8 56 0 6.00 $0.9000
D14 v2 Memory optimized 8 16 112 0 12.00 $1.8000
E4 v3 Memory optimized 2 4 32 0 3.33 $0.5000
E8 v3 Memory optimized 4 8 64 0 6.67 $1.0000
E16 v3 Memory optimized 8 16 128 0 13.33 $2.0000
E32 v3 Memory optimized 16 32 256 0 26.67 $4.0000
E64 v3 Memory optimized 32 64 432 0 46.67 $7.0000
E4s v3 Memory optimized 2 4 32 0 3.33 $0.5000
E8s v3 Memory optimized 4 8 64 0 6.67 $1.0000
E16s v3 Memory optimized 8 16 128 0 13.33 $2.0000
E16-8s v3 Memory optimized 4 8 128 0 12.00 $1.8000
E20s v3 Memory optimized 10 20 160 0 16.67 $2.5000
E32s v3 Memory optimized 16 32 256 0 26.67 $4.0000
E48s v3 Memory optimized 24 48 384 0 40.00 $6.0000
E64s v3 Memory optimized 32 64 432 0 46.67 $7.0000
E8a v4 Memory optimized 4 8 64 0 6.67 $1.0000
E16a v4 Memory optimized 8 16 128 0 13.33 $2.0000
E32a v4 Memory optimized 16 32 256 0 26.67 $4.0000
E64a v4 Memory optimized 32 64 512 0 53.33 $8.0000
E4s v4 Memory optimized 2 4 32 0 3.33 $0.5000
E8s v4 Memory optimized 4 8 64 0 6.67 $1.0000
E16s v4 Memory optimized 8 16 128 0 13.33 $2.0000
E20s v4 Memory optimized 10 20 160 0 16.67 $2.5000
E32s v4 Memory optimized 16 32 256 0 26.67 $4.0000
E48s v4 Memory optimized 24 48 384 0 40.00 $6.0000
E64s v4 Memory optimized 32 64 504 0 52.67 $7.9000
E4ds v4 Memory optimized 2 4 32 0 3.33 $0.5000
E8ds v4 Memory optimized 4 8 64 0 6.67 $1.0000
E16ds v4 Memory optimized 8 16 128 0 13.33 $2.0000
E20ds v4 Memory optimized 10 20 160 0 16.67 $2.5000
E32ds v4 Memory optimized 16 32 256 0 26.67 $4.0000
E48ds v4 Memory optimized 24 48 384 0 40.00 $6.0000
E64ds v4 Memory optimized 32 64 504 0 52.67 $7.9000
E4a v4 Memory optimized 2 4 32 0 3.33 $0.5000
E4as v5 Memory optimized 2 4 32 0 3.33 $0.5000
E8as v5 Memory optimized 4 8 64 0 6.67 $1.0000
E16as v5 Memory optimized 8 16 128 0 13.33 $2.0000
E20as v5 Memory optimized 10 20 160 0 16.67 $2.5000
E32as v5 Memory optimized 16 32 256 0 26.67 $4.0000
E48as v5 Memory optimized 24 48 384 0 40.00 $6.0000
E64as v5 Memory optimized 32 64 512 0 53.33 $8.0000
               
F8s v2 Compute optimized 4 8 16 0 2.67 $0.4000
F16s v2 Compute optimized 8 16 32 0 5.33 $0.8000
F32s v2 Compute optimized 16 32 64 0 10.67 $1.6000
               
L8s v2 Storage optimized 4 8 64 0 6.67 $1.0000
L16s v2 Storage optimized 8 16 128 0 13.33 $2.0000
L32s v2 Storage optimized 16 32 256 0 26.67 $4.0000
L48s v2 Storage optimized 24 48 384 0 40.00 $6.0000
               
NC6 GPU optimized 3 6 56 1 5.67 $0.8500
NC24r GPU optimized 12 24 224 4 22.67 $3.4000
NC6s v3 GPU optimized 3 6 112 1 10.33 $1.5500
NC24s v3 GPU optimized 12 24 448 4 41.33 $6.2000

Operational Database - Azure instances

               
Instance* Category Cores vCPUs RAM GPU CCUs Rate/hr
D8 v3 General Purpose 4 8 32 0 4.00 $0.3200
D16 v3 General Purpose 8 16 64 0 8.00 $0.6400
D32 v3 General Purpose 16 32 128 0 16.00 $1.2800
D8s v3 General Purpose 4 8 32 0 4.00 $0.3200
D32s v3 General Purpose 16 32 128 0 16.00 $1.2800
D8a v4 General Purpose 4 8 32 0 4.00 $0.3200
D32a v4 General Purpose 16 32 128 0 16.00 $1.2800
D64a v4 General purpose 32 64 256 0 32.00 $2.5600
               
E32s v3 Memory optimized 16 32 256 0 26.67 $2.1333
               
L8s v2 Storage Optimized 4 8 64 0 6.67 $0.5333
L8as v3 Storage optimized 4 8 64 0 6.67 $0.5333

* Instance type is auto-selected by Operational Database based on workload needs

DataFlow Deployments & Test Sessions - Azure instances

Node Type vCPUs Memory GPU CCUs Rate/hr
Extra Small 2 4 0 0.67 $0.2000
Small 3 6 0 1.00 $0.3000
Medium 6 12 0 2.00 $0.6000
Large 12 24 0 4.00 $1.2000
*Note: Test Sessions always use the Extra Small node type

DataFlow Functions - Azure

Total Billable Invocations per Flow/Month Price per Billable Invocation

First 1,000 Billable Invocations

$0.1000

Next 9,000 Billable Invocations

$0.0200

Next 90,000 Billable Invocations

$0.0020

Next 900,000 Billable Invocations

$0.0003

Over 1,000,001 Billable Invocations

$0.0001

*Notes:
  • Pricing Volume Tiers are per individual DataFlow Function
  • The volume table above is a tiered volume table, where the first 1,000 invocations are always charged at $0.10 per month, the next 9,000 invocations per month are charged at $0.02 per month and so on
  • “Billable invocation” is a combination of function invocations and function duration. Every time an instance of DataFlow Functions is invoked that counts as one Billable Invocation. If a DFF runs for more than one second, each subsequent second (after the initial second) counts as another Billable Invocation.  In addition, if a DFF invocation runs for less than one second, each fractional second will count as one Billable Invocation.

Data Hub - GCP Instances

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr
e2-standard-2 General Purpose 1 2 8 0 1.00 $0.0400
e2-standard-4 General Purpose 2 4 16 0 2.00 $0.0800
e2-standard-8 General Purpose 4 8 32 0 4.00 $0.1600
e2-standard-16 General Purpose 8 16 64 0 8.00 $0.3200
e2-standard-32 General Purpose 16 32 128 0 16.00 $0.6400
n1-standard-2 General Purpose 1 2 7.5 0 0.96 $0.0383
n1-standard-4 General Purpose 2 4 15 0 1.92 $0.0767
n1-standard-8 General Purpose 4 8 30 0 3.83 $0.1533
n1-standard-16 General Purpose 8 16 60 0 7.67 $0.3067
n1-standard-32 General Purpose 16 32 120 0 15.33 $0.6133
n1-standard-64 General Purpose 32 64 240 0 30.67 $1.0000
n2-standard-2 General Purpose 1 2 8 0 1.00 $0.0400
n2-standard-4 General Purpose 2 4 16 0 2.00 $0.0800
n2-standard-8 General Purpose 4 8 32 0 4.00 $0.1600
n2-standard-16 General Purpose 8 16 64 0 8.00 $0.3200
n2-standard-32 General Purpose 16 32 128 0 16.00 $0.6400
n2-standard-48 General Purpose 24 48 192 0 24.00 $0.9600
n2-standard-64 General Purpose 32 64 256 0 32.00 $1.0000
n2-standard-80 General Purpose 40 80 320 0 40.00 $1.0000
n2d-standard-2 General Purpose 1 2 8 0 1.00 $0.0400
n2d-standard-4 General Purpose 2 4 16 0 2.00 $0.0800
n2d-standard-8 General Purpose 4 8 32 0 4.00 $0.1600
n2d-standard-16 General Purpose 8 16 64 0 8.00 $0.3200
n2d-standard-32 General Purpose 16 32 128 0 16.00 $0.6400
n2d-standard-48 General Purpose 24 48 192 0 24.00 $0.9600
n2d-standard-64 General Purpose 32 64 256 0 32.00 $1.0000
n2d-standard-80 General Purpose 40 80 320 0 40.00 $1.0000
               
e2-highmem-8 High Memory 4 8 64 0 6.67 $0.2667
e2-highmem-16 High Memory 8 16 128 0 13.33 $0.5333
n2d-highmem-16 High Memory 8 16 128 0 13.33 $0.5333
n2d-highmem-32 High Memory 16 32 256 0 26.67 $1.0000
n2d-highmem-64 High Memory 32 64 512 0 53.33 $1.0000
               
e2-highcpu-8 High Compute 4 8 8 0 2.00 $0.0800
e2-highcpu-16 High Compute 8 16 16 0 4.00 $0.1600
e2-highcpu-32 High Compute 16 32 32 0 8.00 $0.3200
n2d-highcpu-8 High Compute 4 8 8 0 2.00 $0.0800
n2d-highcpu-16 High Compute 8 16 16 0 4.00 $0.1600
n2d-highcpu-32 High Compute 16 32 32 0 8.00 $0.3200

Data Hub - Flow Management - GCP Instances

 

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr*
e2-standard-2 General Purpose 1 2 8 0 1.00 $0.1500
e2-standard-4 General Purpose 2 4 16 0 2.00 $0.3000
e2-standard-8 General Purpose 4 8 32 0 4.00 $0.6000
e2-standard-16 General Purpose 8 16 64 0 8.00 $1.2000
e2-standard-32 General Purpose 16 32 128 0 16.00 $2.4000
n1-standard-2 General Purpose 1 2 7.5 0 0.96 $0.1438
n1-standard-4 General Purpose 2 4 15 0 1.92 $0.2875
n1-standard-8 General Purpose 4 8 30 0 3.83 $0.5750
n1-standard-16 General Purpose 8 16 60 0 7.67 $1.1500
n1-standard-32 General Purpose 16 32 120 0 15.33 $2.3000
n1-standard-64 General Purpose 32 64 240 0 30.67 $4.6000
n2-standard-2 General Purpose 1 2 8 0 1.00 $0.1500
n2-standard-4 General Purpose 2 4 16 0 2.00 $0.3000
n2-standard-8 General Purpose 4 8 32 0 4.00 $0.6000
n2-standard-16 General Purpose 8 16 64 0 8.00 $1.2000
n2-standard-32 General Purpose 16 32 128 0 16.00 $2.4000
n2-standard-48 General Purpose 24 48 192 0 24.00 $3.6000
n2-standard-64 General Purpose 32 64 256 0 32.00 $4.8000
n2-standard-80 General Purpose 40 80 320 0 40.00 $6.0000
n2d-standard-2 General Purpose 1 2 8 0 1.00 $0.1500
n2d-standard-4 General Purpose 2 4 16 0 2.00 $0.3000
n2d-standard-8 General Purpose 4 8 32 0 4.00 $0.6000
n2d-standard-16 General Purpose 8 16 64 0 8.00 $1.2000
n2d-standard-32 General Purpose 16 32 128 0 16.00 $2.4000
n2d-standard-48 General Purpose 24 48 192 0 24.00 $3.6000
n2d-standard-64 General Purpose 32 64 256 0 32.00 $4.8000
n2d-standard-80 General Purpose 40 80 320 0 40.00 $6.0000
               
e2-highmem-8 High Memory 4 8 64 0 6.67 $1.0000
e2-highmem-16 High Memory 8 16 128 0 13.33 $2.0000
n2d-highmem-16 High Memory 8 16 128 0 13.33 $2.0000
n2d-highmem-32 High Memory 16 32 256 0 26.67 $4.0000
n2d-highmem-64 High Memory 32 64 512 0 53.33 $8.0000
               
e2-highcpu-8 High Compute 4 8 8 0 2.00 $0.3000
e2-highcpu-16 High Compute 8 16 16 0 4.00 $0.6000
e2-highcpu-32 High Compute 16 32 32 0 8.00 $1.2000
n2d-highcpu-8 High Compute 4 8 8 0 2.00 $0.3000
n2d-highcpu-16 High Compute 8 16 16 0 4.00 $0.6000
n2d-highcpu-32 High Compute 16 32 32 0 8.00 $1.2000

Operational Database - GCP Instances

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr*
n2-standard-8 General Purpose 4 8 32 0 4.00 $0.3200
n2-standard-16 General Purpose 8 16 64 0 8.00 $0.6400
n2-standard-32 General Purpose 16 32 128 0 16.00 $1.2800
               
n2d-highmem-32 High Memory 16 32 256 0 26.67 $2.1333

DataFlow Functions - GCP

Total Billable Invocations per Flow/Month Price per Billable Invocation

First 1,000 Billable Invocations

$0.1000

Next 9,000 Billable Invocations

$0.0200

Next 90,000 Billable Invocations

$0.0020

Next 900,000 Billable Invocations

$0.0003

Over 1,000,001 Billable Invocations

$0.0001

*Notes:
  • Pricing Volume Tiers are per individual DataFlow Function
  • The volume table above is a tiered volume table, where the first 1,000 invocations are always charged at $0.10 per month, the next 9,000 invocations per month are charged at $0.02 per month and so on
  • “Billable invocation” is a combination of function invocations and function duration. Every time an instance of DataFlow Functions is invoked that counts as one Billable Invocation. If a DFF runs for more than one second, each subsequent second (after the initial second) counts as another Billable Invocation.  In addition, if a DFF invocation runs for less than one second, each fractional second will count as one Billable Invocation.

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