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Cloudian and AI platform WEKA integrate to tackle big data while strengthening APAC partnership
Fri, 21st Jan 2022
FYI, this story is more than a year old

Cloudian has announced the integration of its HyperStore object storage with the WEKA data platform for AI, providing exabyte-scalable private cloud storage for processing iterative analytical workloads.

The company says the combined solution unifies and simplifies the data pipeline for performance-intensive workloads and accelerated DataOps, all managed under a single namespace. The new solution also reduces the storage TCO associated with data analytics by a third, compared to traditional storage systems.

Advanced analytic workloads create data storage challenges

"Organisations are consuming and creating more data than ever before, and many are applying AI, machine learning and other advanced analytics to make better decisions in real-time and unlock new revenue streams," says Cloudian.

These analytics workloads create and use massive data sets that pose significant storage challenges. Most importantly, the ability to manage the data growth and enable users to extract timely insights from that data. The company says traditional storage systems can't handle the processing needs or the scalability required for iterative analytics workloads and introduce bottlenecks to productivity and data-driven decision-making.

Together, Cloudian and WEKA enable organisations to overcome the challenges of accelerating and scaling their data pipelines while lowering data analytics storage costs," says Cloudian director, ANZ, Oceania, and ASEAN, James Wright.

"WEKA's data platform, built on WekaFS, addresses the storage challenges posed by today's enterprise AI workloads and other high-performance applications running on-premises, in the cloud or bursting between platforms."

He says the joint solution offers the simplicity of NAS, the performance of SAN or DAS and the scale of object storage, along with accelerating every stage of the data pipeline from data ingestion to cleansing to modelled results.

Integrated through WEKA's tiering function, Cloudian's enterprise-grade, software-defined object storage provides the following key benefits:

  • Run concurrent workloads while eliminating compute cluster bottlenecks and reducing processing times.
  • Grow deployments on demand, from terabytes to an exabyte without disruption, achieving the flexibility and elasticity of the public cloud within a private data center or hybrid cloud model.
  • Protect data with encryption in flight and at rest, integrated firewall, RBAC/IAM and SAML access controls, and certification with the most rigorous regulatory requirements, such as Common Criteria, FIPS and SEC Rule 17a-4(f).
  • Achieve high data durability with the option to protect and distribute data using replication or erasure coding, thereby eliminating the need for a separate data backup process.
  • Provision multiple users on shared infrastructure without compromising security.
  • Save on storage costs, as the solution runs on standard x86 hardware with local NVMe SSDs.

"Cloudian and WEKA share a strong partnership in Australia and New Zealand, working with local resellers and service providers such as CSW-IT, NTT and Perfekt, and solving big data challenges for healthcare organisations, research facilities, universities, and geological organisations," says Wright.
 
"This integration will take that partnership to the next level across the region. Together, we can support increasingly large data lakes and pools, supercomputing, and even quantum computing capabilities soon, helping ANZ organisations map genomic sequencing, model outcomes using AI, and much more."

Jonathan Martin, president of WEKA, says, "As organisations increasingly employ AI, ML and other advanced analytics to extract greater value from their data, they require a modern storage platform that enables fast, easy data processing and management.

"The combination of the WEKA Data Platform and Cloudian object storage provides an ideal solution that can seamlessly and cost-effectively scale to meet growing demands."