Weka

Weka is a high-performance data platform designed to support AI, machine learning, and high-performance computing (HPC) workloads at scale. Its primary purpose is to provide a unified, software-defined storage architecture that delivers low-latency, high-throughput access to data across on-premises, cloud, and hybrid environments. By optimizing data pipelines for GPU-accelerated and agentic AI workloads, Weka helps organizations remove I/O bottlenecks and fully utilize their compute resources.

Weka’s core capabilities include a distributed, parallel file system that delivers NVMe-class performance over standard hardware, enabling rapid access to large training datasets and model artifacts. It supports POSIX, NFS, SMB, and S3 interfaces, allowing seamless integration with existing AI/ML frameworks, data pipelines, and analytics tools. Advanced data services such as snapshots, cloning, tiering to object storage, and data reduction help manage large-scale datasets efficiently while controlling storage costs. The platform is designed for linear scalability, high availability, and consistent performance, even under intensive, mixed workloads.