The modern storage foundation for analytics and AI.
Modernize beyond HDFS: Scale to billions of objects and support 5x denser storage nodes to dramatically lower your TCO.
Unify all workloads: Run S3-native AI and cloud applications alongside your existing Spark and Hive analytic jobs on one platform.
Improve resilience and efficiency: Cut storage overhead by 50% with erasure coding and ensure high availability with a modern architecture.
Breaks the 400-million-file limit of Hadoop Distributed File System (HDFS). Natively scales to 10-billion objects and beyond, solving the "small files problem" for good.
Provides a native S3 API for modern AI/ML workloads (TensorFlow, PyTorch) and a Hadoop-compatible file system for existing analytics (Spark, Hive).
Move from 100TB HDFS nodes to 500TB+ nodes. This 5x density drastically reduces your data center footprint, power, and cooling costs.
Replace 3x data replication with efficient erasure coding (e.g., RS 6+3), cutting your storage overhead by 50% or more while maintaining data durability.
Features an Active-Active architecture for metadata, eliminating the HDFS NameNode bottleneck and enabling much faster cluster restarts and recovery.
Create instantaneous, bucket-level snapshots for point-in-time backup, disaster recovery, and compliance with no performance impact.
See how industry leaders scale past HDFS with Cloudera Object Store.
technology
PCSS
telecommunications
Deutsche Telekom
manufacturing and automotive
Vodafone
Take the next step
Dive deeper into the technical architecture and see the clear, step-by-step migration path from HDFS to Cloudera Object Store..
Cloudera Object Store documentation
Get an in-depth technical overview of Cloudera Object Store (Ozone) architecture, components, and security.
HDFS Migration Guide
Get a technical, step-by-step guide to migrating your existing data from HDFS to Cloudera Object Store.
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