ALLUXIO COMMUNITY OFFICE HOUR
Users deploy Alluxio in a wide range of use cases from analytics to AI platforms, for Alluxio’s unified access to data and transparent caching for acceleration. However, many frameworks are SQL engines, like Presto, Apache Spark SQL, or Apache Hive, and consume data structured as tables of rows and columns. Since Alluxio is commonly used as a filesystem of files and directories, there is a mismatch between how Alluxio exposes data (files, directories), and how SQL engines deal with data (tables, rows, columns). This gap creates various challenges and inefficiencies.
Therefore, in the Alluxio 2.1 release, we introduce Alluxio Structured Data Management, which is a new set of services that enables structured data applications to interact with data more efficiently. The new services include the catalog service and a transformation service, which all work together to bridge the gap between storage and SQL engines and enable physical data independence.
In this office hour, we introduce the concepts and components of Alluxio Structured Data Management, and go through a demo with Presto.
In this Office Hour we’ll go over:
- Introduction and motivation of Alluxio Structured Data Management
- Overview of the different services of Alluxio Structured Data Management in Alluxio 2.1
- A demo of using Alluxio Structured Data Management with Presto
ALLUXIO COMMUNITY OFFICE HOUR
Users deploy Alluxio in a wide range of use cases from analytics to AI platforms, for Alluxio’s unified access to data and transparent caching for acceleration. However, many frameworks are SQL engines, like Presto, Apache Spark SQL, or Apache Hive, and consume data structured as tables of rows and columns. Since Alluxio is commonly used as a filesystem of files and directories, there is a mismatch between how Alluxio exposes data (files, directories), and how SQL engines deal with data (tables, rows, columns). This gap creates various challenges and inefficiencies.
Therefore, in the Alluxio 2.1 release, we introduce Alluxio Structured Data Management, which is a new set of services that enables structured data applications to interact with data more efficiently. The new services include the catalog service and a transformation service, which all work together to bridge the gap between storage and SQL engines and enable physical data independence.
In this office hour, we introduce the concepts and components of Alluxio Structured Data Management, and go through a demo with Presto.
In this Office Hour we’ll go over:
- Introduction and motivation of Alluxio Structured Data Management
- Overview of the different services of Alluxio Structured Data Management in Alluxio 2.1
- A demo of using Alluxio Structured Data Management with Presto
Videos:
Presentation Slides:
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Videos
Amazon S3 and other cloud object stores have become the de facto storage system for organizations large and small. And it’s no wonder why. Cloud object stores deliver unprecedented flexibility with unlimited capacity that scales on demand and ensures data durability out-of-the-box at unbeatable prices.
Yet as workloads shift toward real-time AI, inference, feature stores, and agentic memory systems, S3’s latency and limited semantics begin to show their limits. In this webinar, you’ll learn how to augment — rather than replace — S3 with a tiered architecture that restores sub-millisecond performance, richer semantics, and high throughput — all while preserving S3’s advantages of low-cost capacity, durability, and operational simplicity.
We’ll walk through:
- The key challenges posed by latency-sensitive, semantically rich workloads (e.g. feature stores, RAG pipelines, write-ahead logs)
- Why “just upgrading storage” isn’t sufficient — the bottlenecks in metadata, object access latency, and write semantics
- How Alluxio transparently layers on top of S3 to provide ultra-low latency caching, append semantics, and zero data migration with both FSx-style POSIX access and S3 API access
- Real-world results: achieving sub-ms TTFB, 90%+ GPU utilization in ML training, 80X faster feature store query response times, and dramatic cost savings from reduced S3 operations
- Trade-offs, deployment patterns, and best practices for integrating this tiered approach in your AI/analytics stack
Pratik Mishra delivered insights on architecting scalable, deployable, and resilient AI infrastructure at scale. His discussion on fault tolerance, checkpoint optimization, and the democratization of AI compute through AMD's open ecosystem resonated strongly with the challenges teams face in production ML deployments.
In this talk, Bin Fan, VP of Technology at Alluxio, presents on building tiered architectures that bring sub-millisecond latency to S3-based workloads. The comparison showing Alluxio's 45x performance improvement over S3 Standard and 5x over S3 Express One Zone demonstrated the critical role the performance & caching layer plays in modern AI infrastructure.