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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 Rate/hr
m5.2xlarge General purpose 4 8 32 0 4.00 $0.2800
m5.4xlarge General purpose 8 16 64 0 8.00 $0.5600
m5.8xlarge General purpose 16 32 128 0 16.00 $1.1200
m5.16xlarge General purpose 32 64 256 0 32.00 $2.2400
m5.24xlarge General purpose 48 96 384 0 48.00 $3.3600
m5a.2xlarge General purpose 4 8 32 0 4.00 $0.2800
m5a.4xlarge General purpose 8 16 64 0 8.00 $0.5600
m5a.8xlarge General purpose 16 32 128 0 16.00 $1.1200
m5a.16xlarge General purpose 32 64 256 0 32.00 $2.2400
m5a.24xlarge General purpose 48 96 384 0 48.00 $3.3600
m5ad.2xlarge General purpose 4 8 32 0 4.00 $0.2800
m5ad.4xlarge General purpose 8 16 64 0 8.00 $0.5600
m5ad.8xlarge General purpose 16 32 128 0 16.00 $1.1200
m5ad.24xlarge General purpose 48 96 384 0 48.00 $3.3600
m5d.2xlarge General purpose 4 8 32 0 4.00 $0.2800
m5d.4xlarge General purpose 8 16 64 0 8.00 $0.5600
m5d.8xlarge General purpose 16 32 128 0 16.00 $1.1200
m5d.16xlarge General purpose 32 64 256 0 32.00 $2.2400
m5d.24xlarge General purpose 48 96 384 0 48.00 $3.3600
               
r5.2xlarge Memory optimized 4 8 64 0 6.67 $0.4667
r5.4xlarge Memory optimized
8 16 128 0 13.33 $0.9333
r5.8xlarge Memory optimized
16 32 256 0 26.67 $1.8667
r5.16xlarge Memory optimized
32 64 512 0 53.33 $3.7333
r5.24xlarge Memory optimized 48 96 768 0 80.00 $5.6000
r5a.2xlarge Memory optimized 4 8 64 0 6.67 $0.4667
r5a.4xlarge Memory optimized 8 16 128 0 13.33 $0.9333
r5a.8xlarge Memory optimized 16 32 256 0 26.67 $1.8667
r5a.16xlarge Memory optimized 32 64 512 0 53.33 $3.7333
r5a.24xlarge Memory optimized 48 96 768 0 80.00 $5.6000
r5ad.2xlarge Memory optimized 4 8 64 0 6.67 $0.4667
r5ad.4xlarge Memory optimized 8 16 128 0 13.33 $0.9333
r5ad.8xlarge Memory optimized 16 32 256 0 26.67 $1.8667
r5ad.24xlarge Memory optimized 48 96 768 0 80.00 $5.6000
r5d.2xlarge Memory optimized 4 8 64 0 6.67 $0.4667
r5d.4xlarge Memory optimized 8 16 128 0 13.33 $0.9333
r5d.8xlarge Memory optimized 16 32 256 0 26.67 $1.8667
r5d.16xlarge Memory optimized 32 64 512 0 53.33 $3.7333
r5d.24xlarge Memory optimized 48 96 768 0 80.00 $5.6000
               
c5.2xlarge Compute optimized 4 8 16 0 2.67 $0.1867
c5.4xlarge Compute optimized
8 16 32 0 5.33 $0.3733
c5.9xlarge Compute optimized
18 36 72 0 12.00 $0.8400
c5.12xlarge Compute optimized
24 48 96 0 16.00 $1.1200
c5.24xlarge Compute optimized
48 96 192 0 32.00 $2.2400
c5ad.2xlarge Compute optimized
4 8 16 0 2.67 $0.1867
c5ad.4xlarge Compute optimized
8 16 32 0 5.33 $0.3733
c5a.2xlarge Compute optimized
4 8 16 0 2.67 $0.1867
c5a.4xlarge Compute optimized
8 16 32 0 5.33 $0.3733
c5d.2xlarge Compute optimized
4 8 16 0 2.67 $0.1867
c5d.4xlarge Compute optimized
8 16 32 0 5.33 $0.3733
c5d.9xlarge Compute optimized
18 36 72 0 12.00 $0.8400
               
i3.2xlarge Storage optimized 4 8 61 0 6.42 $0.4492
i3.4xlarge Storage optimized
8 16 122 0 12.83 $0.8983
i3.8xlarge Storage optimized
16 32 244 0 25.67 $1.7967

Data Warehouse - AWS instances

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr
r5d.4xlarge Memory optimized 8 16 128 0 13.33 $0.7200

Machine Learning - AWS instances

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr
m4.large General purpose 1 2 8 0 1.00 $0.2000
m4.xlarge General purpose
2 4 16 0 2.00 $0.4000
m4.2xlarge General purpose
4 8 32 0 4.00 $0.8000
m4.4xlarge General purpose
8 16 64 0 8.00 $1.6000
m4.10xlarge General purpose 20 40 160 0 20.00 $4.0000
m4.16xlarge General purpose 32 64 256 0 32.00 $6.4000
m5.large General purpose 1 2 8 0 1.00 $0.2000
m5.xlarge General purpose 2 4 16 0 2.00 $0.4000
m5.2xlarge General purpose 4 8 32 0 4.00 $0.8000
m5.4xlarge General purpose 8 16 64 0 8.00 $1.6000
m5.8xlarge General purpose 16 32 128 0 16.00 $3.2000
m5.12xlarge General purpose 24 48 192 0 24.00 $4.8000
m5.24xlarge General purpose 48 96 384 0 48.00 $9.6000
m5d.large General purpose 1 2 8 0 1.00 $0.2000
m5d.xlarge General purpose 2 4 16 0 2.00 $0.4000
m5d.2xlarge General purpose 4 8 32 0 4.00 $0.8000
m5d.4xlarge General purpose 8 16 64 0 8.00 $1.6000
m5d.12xlarge General purpose 24 48 192 0 24.00 $4.8000
m5d.24xlarge General purpose 48 96 384 0 48.00 $9.6000
m5a.large General purpose 1 2 8 0 1.00 $0.2000
m5a.xlarge General purpose 2 4 16 0 2.00 $0.4000
m5a.2xlarge General purpose 4 8 32 0 4.00 $0.8000
m5a.4xlarge General purpose 8 16 64 0 8.00 $1.6000
m5a.8xlarge General purpose 16 32 128 0 16.00 $3.2000
m5a.12xlarge General purpose 24 48 192 0 24.00 $4.8000
m5a.16xlarge General purpose 32 64 256 0 32.00 $6.4000
m5a.24xlarge General purpose 48 96 384 0 48.00 $9.6000
               
r3.xlarge Memory optimized 2 4 31 0 3.25 $0.6500
r3.2xlarge Memory optimized 4 8 61 0 6.42 $1.2833
r3.4xlarge Memory optimized 8 16 122 0 12.83 $2.5667
r3.8xlarge Memory optimized 16 32 244 0 25.67 $5.1333
r4.xlarge Memory optimized 2 4 31 0 3.25 $0.6500
r4.2xlarge Memory optimized 4 8 61 0 6.42 $1.2833
r4.4xlarge Memory optimized 8 16 122 0 12.83 $2.5667
r4.8xlarge Memory optimized 16 32 244 0 25.67 $5.1333
r4.16xlarge Memory optimized 32 64 488 0 51.33 $10.2667
r5.large Memory optimized 1 2 16 0 1.67 $0.3333
r5.xlarge Memory optimized 2 4 32 0 3.33 $0.6667
r5.2xlarge Memory optimized 4 8 64 0 6.67 $1.3333
r5.4xlarge Memory optimized 8 16 128 0 13.33 $2.6667
r5.8xlarge Memory optimized 16 32 256 0 26.67 $5.3333
r5.12xlarge Memory optimized 24 48 384 0 40.00 $8.0000
r5.16xlarge Memory optimized 32 64 512 0 53.33 $10.6667
r5.24xlarge Memory optimized 48 96 768 0 80.00 $16.0000
r5d.large Memory optimized 1 2 16 0 1.67 $0.3333
r5d.xlarge Memory optimized 2 4 32 0 3.33 $0.6667
r5d.2xlarge Memory optimized 4 8 64 0 6.67 $1.3333
r5d.4xlarge Memory optimized 8 16 128 0 13.33 $2.6667
r5d.12xlarge Memory optimized 24 48 384 0 40.00 $8.0000
r5d.24xlarge Memory optimized 48 96 768 0 80.00 $16.0000
r5a.large Memory optimized 1 2 16 0 1.67 $0.3333
r5a.xlarge Memory optimized 2 4 32 0 3.33 $0.6667
r5a.2xlarge Memory optimized 4 8 64 0 6.67 $1.3333
r5a.4xlarge Memory optimized 8 16 128 0 13.33 $2.6667
r5a.8xlarge Memory optimized 16 32 256 0 26.67 $5.3333
r5a.12xlarge Memory optimized 24 48 384 0 40.00 $8.0000
r5a.16xlarge Memory optimized 32 64 512 0 53.33 $10.6667
r5a.24xlarge Memory optimized 48 96 768 0 80.00 $16.0000
z1d.large Memory optimized 1 2 16 0 1.67 $0.3333
z1d.xlarge Memory optimized 2 4 32 0 3.33 $0.6667
z1d.2xlarge Memory optimized 4 8 64 0 6.67 $1.3333
z1d.3xlarge Memory optimized 6 12 96 0 10.00 $2.0000
z1d.6xlarge Memory optimized 12 24 192 0 20.00 $4.0000
z1d.12xlarge Memory optimized 24 48 384 0 40.00 $8.0000
               
c4.2xlarge Compute optimized 4 8 15 0 2.58 $0.5167
c4.4xlarge Compute optimized 8 16 30 0 5.17 $1.0333
c4.8xlarge Compute optimized 18 36 60 0 11.00 $2.2000
c5.xlarge Compute optimized 2 4 8 0 1.33 $0.2667
c5.2xlarge Compute optimized 4 8 16 0 2.67 $0.5333
c5.4xlarge Compute optimized 8 16 32 0 5.33 $1.0667
c5.9xlarge Compute optimized 18 36 72 0 12.00 $2.4000
c5.18xlarge Compute optimized 36 72 144 0 24.00 $4.8000
c5d.xlarge Compute optimized 2 4 8 0 1.33 $0.2667
c5d.2xlarge Compute optimized 4 8 16 0 2.67 $0.5333
c5d.4xlarge Compute optimized 8 16 32 0 5.33 $1.0667
c5d.9xlarge Compute optimized 18 36 72 0 12.00 $2.4000
c5d.18xlarge Compute optimized 36 72 144 0 24.00 $4.8000
               
i3.xlarge Storage optimized 2 4 31 0 3.25 $0.6500
i3.2xlarge Storage optimized 4 8 61 0 6.42 $1.2833
i3.4xlarge Storage optimized 8 16 122 0 12.83 $2.5667
i3.8xlarge Storage optimized 16 32 244 0 25.67 $5.1333
i3.16xlarge Storage optimized 32 64 488 0 51.33 $10.2667
i2.xlarge Storage optimized 2 4 31 0 3.25 $0.6500
i2.2xlarge Storage optimized 4 8 61 0 6.42 $1.2833
i2.4xlarge Storage optimized 8 16 122 0 12.83 $2.5667
i2.8xlarge Storage optimized 16 32 244 0 25.67 $5.1333
               
p2.xlarge GPU optimized 2 4 61 1 5.75 $0.9363
p2.8xlarge GPU optimized 8 16 488 8 43.33 $7.4900
p2.16xlarge GPU optimized 16 32 732 16 66.33 $12.1333
p3.2xlarge GPU optimized 4 8 61 1 6.42 $1.8358
p3.8xlarge GPU optimized 16 32 244 4 25.67 $7.3444
p3.16xlarge GPU optimized 32 64 488 8 51.33 $14.6867
p3dn.24xlarge GPU Optimized 48 96 768 8 80.00 $18.7000
p4dn.24xlarge GPU Optimized 48 96 1152 8 112.00 $25.0400
g4dn.xlarge GPU Optimized 2 4 16 1 2.00 $0.5200
g4dn.2xlarge GPU Optimized 4 8 32 1 4.00 $0.8000
g4dn.4xlarge GPU Optimized 8 16 64 1 8.00 $1.3600
g4dn.8xlarge GPU Optimized 16 32 128 1 16.00 $2.4800
g4dn.12xlarge GPU Optimized 24 48 192 4 24.00 $4.3200
g4dn.16xlarge GPU Optimized 32 64 256 1 32.00 $4.7200
g4dn.metal GPU Optimized 48 96 384 8 48.00 $8.6400

Data Hub - AWS instances

 Instance Category Cores vCPUs RAM GPU CCUs Data Hub Rate/hr
m5.xlarge General purpose
2 4 16 0 2.00 $0.0800
m5.2xlarge General purpose 4 8 32 0 4.00 $0.1600
m5.4xlarge General purpose 8 16 64 0 8.00 $0.3200
m5.8xlarge General purpose 16 32 128 0 16.00 $0.6400
m5.12xlarge General purpose 24 48 192 0 24.00 $0.9600
m5.16xlarge General purpose 32 64 256 0 32.00 $1.0000
m5.24xlarge General purpose 48 96 384 0 48.00 $1.0000
m5a.xlarge General purpose 2 4 16 0 2.00 $0.0800
m5a.2xlarge General purpose 4 8 32 0 4.00 $0.1600
m5a.4xlarge General purpose 8 16 64 0 8.00 $0.3200
m5a.8xlarge General purpose 16 32 128 0 16.00 $0.6400
m5a.12xlarge General purpose 24 48 192 0 24.00 $0.9600
m5a.16xlarge General purpose 32 64 256 0 32.00 $1.0000
m5a.24xlarge General purpose 48 96 384 0 48.00 $1.0000
m5n.2xlarge General purpose 4 8 32 0 4.00 $0.1600
m5n.4xlarge General purpose 8 16 64 0 8.00 $0.3200
m5n.8xlarge General purpose 16 32 128 0 16.00 $0.6400
               
r5.2xlarge Memory optimized 4 8 64 0 6.67 $0.2667
r5.4xlarge Memory optimized 8 16 128 0 13.33 $0.5333
r5.8xlarge Memory optimized 16 32 256 0 26.67 $1.0000
r5.16xlarge Memory optimized 32 64 512 0 53.33 $1.0000
r5d.xlarge Memory optimized 2 4 32 0 3.33 $0.1333
r5d.2xlarge Memory optimized 4 8 64 0 6.67 $0.2667
r5d.4xlarge Memory optimized 8 16 128 0 13.33 $0.5333
r5d.8xlarge Memory optimized 16 32 256 0 26.67 $1.0000
r5d.16xlarge Memory optimized 32 64 512 0 53.33 $1.0000
r5n.2xlarge Memory optimized 4 8 64 0 6.67 $0.2667
r5n.4xlarge Memory optimized 8 16 128 0 13.33 $0.5333
r5n.8xlarge Memory optimized 16 32 256 0 26.67 $1.0000
r5n.16xlarge Memory optimized 32 64 512 0 53.33 $1.0000
r5dn.xlarge Memory optimized 2 4 32 0 3.33 $0.1333
r5dn.2xlarge Memory optimized 4 8 64 0 6.67 $0.2667
r5dn.4xlarge Memory optimized 8 16 128 0 13.33 $0.5333
r5dn.8xlarge Memory optimized 16 32 256 0 26.67 $1.0000
r5dn.16xlarge Memory optimized 32 64 512 0 53.33 $1.0000
r5a.4xlarge Memory optimized 8 16 128 0 13.33 $0.5333
r5a.8xlarge Memory optimized 16 32 256 0 26.67 $1.0000
r5ad.xlarge Memory optimized 2 4 32 0 3.33 $0.1333
r5ad.2xlarge Memory optimized 4 8 64 0 6.67 $0.2667
r5ad.4xlarge Memory optimized 8 16 128 0 13.33 $0.5333
r5ad.8xlarge Memory optimized 16 32 256 0 26.67 $1.0000
r5ad.16xlarge Memory optimized 32 64 512 0 53.33 $1.0000
r4.xlarge Memory Optimized 2 4 30.5 0 3.21 $0.1283
r4.2xlarge Memory Optimized 4 8 61 0 6.42 $0.2567
r4.4xlarge Memory Optimized 8 16 122 0 12.83 $0.5133
r4.8xlarge Memory Optimized 16 32 244 0 25.67 $1.0000
x1e.2xlarge Memory optimized 4 8 244 0 21.67 $0.8667
               
c5.2xlarge Compute optimized 4 8 16 0 2.67 $0.1067
c5.4xlarge Compute optimized 8 16 32 0 5.33 $0.2133
c5.9xlarge Compute optimized 18 36 72 0 12.00 $0.4800
c5a.2xlarge Compute optimized 4 8 16 0 2.67 $0.1067
c5a.4xlarge Compute optimized 8 16 32 0 5.33 $0.2133
c5a.8xlarge Compute optimized 16 32 64 0 10.67 $0.4267
               
i3.2xlarge Storage optimized 4 8 61 0 6.42 $0.2567
i3.4xlarge Storage optimized 8 16 122 0 12.83 $0.5133
i3.8xlarge Storage optimized 16 32 244 0 25.67 $1.0000
i3en.2xlarge Storage optimized 4 8 64 0 6.67 $0.2667
i3en.3xlarge Storage optimized 6 12 96 0 10.00 $0.4000
i3en.6xlarge Storage optimized 12 24 192 0 20.00 $0.8000
i3en.12xlarge Storage optimized 24 48 384 0 40.00 $1.0000
h1.2xlarge Storage optimized 4 8 32 0 4.00 $0.1600
h1.4xlarge Storage optimized 8 16 64 0 8.00 $0.3200
h1.8xlarge Storage optimized 16 32 128 0 16.00 $0.6400
d2.xlarge Storage optimized 2 4 30.5 0 3.21 $0.1283
d2.2xlarge Storage optimized 4 8 61 0 6.42 $0.2567
d2.4xlarge Storage optimized 8 16 122 0 12.83 $0.5133
d2.8xlarge Storage optimized 18 36 244 0 26.33 $1.0000
d3.xlarge Storage optimized 2 4 32 0 3.33 $0.1333
d3.2xlarge Storage optimized 4 8 64 0 6.67 $0.2667
d3.4xlarge Storage optimized 8 16 128 0 13.33 $0.5333
d3.8xlarge Storage optimized 16 32 256 0 26.67 $1.0000
d3en.2xlarge Storage optimized 4 8 32 0 4.00 $0.1600
d3en.4xlarge Storage optimized 8 16 64 0 8.00 $0.3200
d3en.6xlarge Storage optimized 12 24 96 0 12.00 $0.4800
d3en.8xlarge Storage optimized 16 32 128 0 16.00 $0.6400
               
p3.2xlarge GPU optimized 4 8 61 1 6.42 $1.1942
p3.8xlarge GPU optimized 16 32 244 4 25.67 $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
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
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
               
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
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.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
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.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.16xlarge Memory optimized 32 64 512 0 53.33 $8.0000
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
               
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
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
               
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
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

              Promotional Pricing
Instance* Category Cores vCPUs RAM GPU CCUs Rate/hr
m5.2xlarge General purpose 4 8 32 0 4.00 $0.3200
m5.8xlarge General purpose 16 32 128 0 16.00 $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 - AWS instances

Node Type vCPUs Memory GPU CCUs Rate/hr
Extra Small 2 4 0 0.67 $0.2000
Small 4 8 0 1.33 $0.4000
Medium 8 16 0 2.67 $0.8000
Large 16 32 0 5.33 $1.6000

Data Engineering - Azure instances

Instance* Category Cores vCPUs RAM GPU CCUs Rate/hr
D8s v4 General Purpose 4 8 32 0 4.00 $0.2800
D16s v4 General Purpose 8 16 64 0 8.00 $0.5600
D32s v4 General Purpose 16 32 128 0 16.00 $1.1200
D64s v4 General Purpose 32 64 256 0 32.00 $2.2400
               
E8s v3 Memory Optimized 4 8 64 0 6.67 $0.4667
E16s v3 Memory Optimized 8 16 128 0 13.33 $0.9333
E32s v3 Memory Optimized 16 32 256 0 26.67 $1.8667
E64s v3 Memory Optimized 32 64 504 0 52.67 $3.6867
E8s v4 Memory Optimized 4 8 64 0 6.67 $0.4667
E16s v4 Memory Optimized 8 16 128 0 13.33 $0.9333
E32s v4 Memory Optimized 16 32 256 0 26.67 $1.8667
E64s v4 Memory Optimized 32 64 504 0 52.67 $3.6867
               
F8s v2 Compute Optimized 4 8 16 0 2.67 $0.1867
F16s v2 Compute Optimized 8 16 32 0 5.33 $0.3733
F32s v2 Compute Optimized 16 32 64 0 10.67 $0.7467
F48s v2 Compute Optimized 24 48 96 0 16.00 $1.1200
F72s v2 Compute Optimized 36 72 144 0 24.00 $1.6800

* 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 General purpose 8 16 128 0 13.33 $0.7200
E16ds v4 General purpose 8 16 128 0 13.33 $0.7200

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 4.00 $0.8000
D16s v3 General purpose 8 16 64 0 8.00 $1.6000
D32s v3 General purpose 16 32 128 0 16.00 $3.2000
D64s v3 General purpose 32 64 256 0 32.00 $6.4000
D8 v3 General purpose 4 8 32 0 4.00 $0.8000
D16 v3 General purpose 8 16 64 0 8.00 $1.6000
D32 v3 General purpose 16 32 128 0 16.00 $3.2000
D64 v3 General purpose 32 64 256 0 32.00 $6.4000
DS12 v2 General purpose 2 4 28 0 3.00 $0.6000
DS13 v2 General purpose 4 8 56 0 6.00 $1.2000
DS14 v2 General purpose 8 16 112 0 12.00 $2.4000
DS15 v2 General purpose 10 20 140 0 15.00 $3.0000
D12 v2 General purpose 2 4 28 0 3.00 $0.6000
D13 v2 General purpose 4 8 56 0 6.00 $1.2000
D14 v2 General purpose 8 16 112 0 12.00 $2.4000
D15 v2 General purpose 10 20 140 0 15.00 $3.0000
               
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 4 8 32 0 4.00 $0.8000
L8s Storage optimized 8 16 64 0 8.00 $1.6000
L16s Storage optimized 16 32 128 0 16.00 $3.2000
L32s Storage optimized 32 64 256 0 32.00 $6.4000
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 24.00 $4.8000
F4 Storage optimized 4 8 8 0 2.00 $0.4000
F8 Storage optimized 8 16 16 0 4.00 $0.8000
F16 Storage optimized 16 32 32 0 8.00 $1.6000
               
H16 High performance 16 32 112 0 14.67 $2.9333
               
NC6 GPU Optimized 6 12 56 1 6.67 $1.0646
NC12 GPU Optimized 12 24 112 2 13.33 $2.1292
NC24 GPU Optimized 24 48 224 4 26.67 $4.2583
NC6s v2 GPU Optimized 6 12 122 1 12.17 $1.8867
NC12s v2 GPU Optimized 12 24 244 2 24.33 $3.7733
NV24s v2 GPU Optimized 24 48 448 4 45.33 $7.5467
NC6s v3 GPU Optimized 6 12 112 1 11.33 $2.5242
NC12s v3 GPU Optimized 12 24 224 2 22.67 $5.0483
NC24s v3 GPU Optimized 24 48 448 4 45.33 $10.0967
NC4as T4 v3 GPU Optimized 2 4 28 1 3.00 $0.66
NC8as T4 v3 GPU Optimized 4 8 56 1 6.00 $1.08
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
NC96asr A100 v4 GPU Optimized 48 96 900 8 91.00 $22.1000

Data Hub - Azure instances

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr
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
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
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
               
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 64 512 0 53.33 $1.0000
E4a v4 Memory optimized 2 4 32 0 3.33 $0.1333
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
E64ds v4 Memory optimized 32 64 504 0 52.67 $1.0000
E8s v3 Memory optimized 4 8 64 0 6.67 $0.2667
E16s v3 Memory optimized 8 16 128 0 13.33 $0.5333
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
D13 v2 Memory optimized 4 8 56 0 6.00 $0.2400
D14 v2 Memory optimized 8 16 112 0 12.00 $0.4800
               
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 24 244 4 24.33 $1.4317

Data Hub - Flow Management - Azure instances

 

Instance Category Cores vCPUs RAM GPU CCUs Rate/hr*
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
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
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
               
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 64 512 0 53.33 $8.0000
E4a v4 Memory optimized 2 4 32 0 3.33 $0.5000
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
E64ds_v4 Memory optimized 32 64 504 0 52.67 $7.9000
E8s v3 Memory optimized 4 8 64 0 6.67 $1.0000
E16s v3 Memory optimized 8 16 128 0 13.33 $2.0000
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
D13 v2 Memory optimized 4 8 56 0 6.00 $0.9000
D14 v2 Memory optimized 8 16 112 0 12.00 $1.8000
               
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 24 244 4 24.33 $3.6500

Operational Database - Azure instances

              Promotional Pricing
Instance* Category Cores vCPUs RAM GPU CCUs Rate/hr
D8 v3 General purpose 4 8 32 0 4.00 $0.3200
D8s v3 General purpose 4 8 32 0 4.00 $0.3200
D32s v3 General purpose 16 32 128 0 16.00 $1.2800

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

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
n2dstandard-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
               
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
n2dstandard-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
               
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

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