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Magnus: A Holistic Approach to Data Management for Large-Scale Machine Learning Workloads

Summary: Magnus is a holistic data-management layer on Apache Iceberg tailored to large-scale ML workloads (wide tables, multimodal) combining resource-efficient storage formats with built-in vector/inverted indexes to speed retrieval. It adds scalable Git-like metadata branching, lightweight merge-on-read upsert, and native LRM/LMM training support; deployed at ByteDance with substantial real-world gains. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
14099
Venue
VLDB
Year
2025
Pagerank
4.1945683e-05
Overall Rank
10,777 | 25.03%
DOI
10.14778/3750601.3750620

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