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InferDB: In-Database Machine Learning Inference Using Indexes

Summary: Uses a discretizing embedding of selected features and an index mapping embedding cells to aggregated model outputs to approximate end-to-end ML inference inside the DB. Replaces preprocessing and model execution with a transform+lookup, cutting latency by orders of magnitude while retaining similar accuracy. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13420
Venue
VLDB
Year
2024
Pagerank
4.9241624e-05
Overall Rank
6,796 | 52.73%
DOI
10.14778/3659437.3659441

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