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WEKA for Oracle Cloud Workloads

The most cost-effective way to accelerate your Oracle Cloud workloads

The WEKA Data Platform for Oracle Cloud

Accelerate performance-intensive applications

WEKA provides a unique parallel architecture than runs on dense storage machines in OCI, enabling you to run your most performance-intensive workloads in OCI with ease.

Reduce cloud data infrastructure costs by 50% or more

WEKA enables you to eliminate multiple storage systems and over-provisioning traditionally required for performance-intensive applications in the cloud, dramatically reducing your total data infrastructure costs.

Drive AI model training and tuning

The WEKA Data Platform delivers high IO, low latency, high bandwidth, and handles random small file IO in a unified solution, delivering the performance and scale required for AI and generative AI workloads.

Maximize GPU Use

WEKA software eliminates storage bottlenecks and solves the “I/O blender” effect to feed your GPUs with data at TBs per second and millions of IOPs.

Simplify Data Operations

WEKA provides Radically Simple Storage™ that eliminates the need to maintain and manage multiple copies of data, move data between storage tiers, or tune storage to meet a performance profile, reducing data operations time by 65% according to ESG.

How it works

WEKA on OCI Sample Architecture

You can deploy WEKA software on a cluster of HPC-optimized bare metal Compute shapes (BM.Optimized3.36) with local SSD to create a high-performance storage layer. The WEKA software can then extend the single namespace to an OCI Object Storage bucket for high-capacity storage at the lowest cost.You can easily add more OCI compute shapes or more OCI Object Storage to scale the WEKA namespace up to support Exabytes of capacity or millions of IOPs of storage performance and scale back down when capacity or performance is not needed. Data stored with your WEKA environment is accessible to applications in your environment through multiple protocols, including NFS, SMB, POSIX, NVDIA GPUDirect, and S3.

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