Enterprises are adopting big data technologies to analyze and derive insight from their growing volumes of structured and unstructured data. A familiar problem is the requirement to analyze data from multiple independent storage silos concurrently. In order to consolidate the data, large enterprises typically use custom solutions or build a data lake. These approaches present additional challenges and can be costly and time consuming. Alluxio helps organizations handle their big data by providing a unified view of all of the data in your enterprise – on premise, in the cloud, or hybrid. Applications access data using a standard interface to a global virtual namespace. Alluxio also employs a memory-centric architecture to enable data access at memory speed. With the combined unification and performance benefits, Alluxio can effectively provide big data federation for organizations by acting as a virtual data lake. We just published a whitepaper that goes into more detail on this common use case, you can access it here:Structured Big Data Federation Using Alluxio.
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Learn about the new features in Alluxio AI 3.8 designed to eliminate two of the most painful bottlenecks in modern AI pipelines. Introducing Alluxio S3 Write Cache, which dramatically reduces object store write latency and improves write-heavy workload performance, and Safetensors Model Loading Acceleration that delivers near-local NVMe throughput for model weight loading

For write-heavy AI and analytics workloads, cloud object storage can become the primary bottleneck. This post introduces how Alluxio S3 Write Cache decouples performance from backend limits, reducing write latency up to 8X - down to ~4–6 ms for concurrent and bursty PUT workloads.

Oracle Cloud Infrastructure has published a technical solution blog demonstrating how Alluxio on Oracle Cloud Infrastructure (OCI) delivers exceptional performance for AI and machine learning workloads, achieving sub-millisecond average latency, near-linear scalability, and over 90% GPU utilization across 350 accelerators.