The Answer for Big Data Storage
Big Data analytics delivers insights, and the bigger the dataset, the more fruitful the analyses. But, with large storage capacity comes large challenges: cost, scalability, and data protection. To derive insight from information, you need affordable, highly-scalable storage that’s simple, reliable, and compatible with the tools you have.
Making Big Data Analytics Smarter with Cloudian and Cloudera
Optimize Your Big Data Analytics Environment for Performance, Scale, and Economics
Improve data insights, data management and data protection for more users with more data within a single platform
Bigger Data. Better Results. Faster. Securely.
As data grows in volume, variety and velocity, so does the capacity required for storage and archive as well as associated infrastructure and operating costs. Combining Cloudera’s Enterprise Data Hub (EDH) with Cloudian’s limitlessly scalable object-based storage platform is a best-in-class solution to address these challenges and enable the Information-Driven Enterprise.
This joint solution provides a complete end-to-end approach to store and access unlimited data with multiple frameworks.
Proven with the Most Popular Big Data Solutions
Cloudian® object storage provides cost-effective, petabyte-scalable storage that can replace or augment existing HDFS clusters for Cloudera, Hortonworks, Amazon EMR, and others. Cloudian HyperStore® makes data analyses simpler, while reducing operational and capital costs. Cloudian HyperStore can emulate HDFS storage for Hadoop and Spark workloads, which allows compute and storage to scale independently in large environments.
With Cloudian, you can efficiently store blocks of any size from 4KB to multiple TB, and can reduce storage footprint with integrated erasure coding and compression. Features such as SSE and SSE-C encryption protect data at rest, while TLS can secure data in flight.
- Certified by HortonWorks
- Scale compute resources independent of storage
- No minimum block size requirement
- Reduces storage footprint with erasure coding
- Increases performance with replicas that mimic HDFS
- Compress data on the backend without altering the format
- Enables data protection and collaboration with replication across sites