Database Paper Browser

Back to papers

Transforming ML Predictive Pipelines into SQL with MASQ

Summary: MASQ compiles trained ML pipelines (scikit-learn) into standard SQL for on-DBMS inference, with no UDFs or vendor-specific syntax. Eliminating data movement, it leverages DBMS governance, security, and auditability for portable deployment across DBMSs (MySQL, SQL Server) and GUI-based evaluation. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6052
Venue
SIGMOD
Year
2021
Pagerank
4.3430376e-05
Overall Rank
9,436 | 34.36%
DOI
10.1145/3448016.3452771

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers