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This talk by Isan Rivkin, R&D Team Leader at Treeverse, explores how to extend S3 object storage capabilities through mounting solutions for AI, ETL, and data exploration workflows. Learn how Amazon S3 Mountpoint provides streamlined access to S3 data directly from applications, making it ideal for large-scale read-heavy applications and data lakes requiring elastic, high-throughput access. Discover how lakeFS, a scalable data version control system over S3, offers mounting capabilities that support rapid prototyping and data exploration with version control, branching, and reproducibility features. Explore how advanced caching and prefetching optimizations in lakeFS Mount enable deep learning projects to access cached data quickly, reducing bottlenecks while maintaining data consistency across versions. Gain insights into choosing the right tools for different stages of your data pipeline, from scalable production workloads to flexible prototyping, to optimize workflows across storage and compute environments.
