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.
Intel Storage Solutions: Analytics using Hadoop and Cloudian
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