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ATLAS: a Small but Complete SQL Extension for Data Mining and Data Streams

Summary: ATLAS is a small but complete SQL extension enabling user-defined aggregates and table functions entirely in SQL, making SQL Turing-complete for data mining and streams. It adds online aggregates (initialize/iterate/terminate in one SQL procedure), stream management, and SQL-based rewrite/optimization, with 20–40% overhead vs C/C++. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9070
Venue
VLDB
Year
2003
Pagerank
4.8973157e-05
Overall Rank
6,878 | 52.16%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
1,532 Data Management in Machine Learning: Challenges, Techniques, and Systems 2017 SIGMOD 0.00011472681
3,378 General Incremental Sliding-Window Aggregation 2015 VLDB 7.1622572e-05
5,117 Sampling Algorithms in a Stream Operator 2005 SIGMOD 5.6825418e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank Cited Paper Year Venue Pagerank
14 Online Aggregation 1997 SIGMOD 0.0010801504
43 Models and Issues in Data Stream Systems 2002 PODS 0.00072723062
9,288 Using SQL to Build New Aggregates and Extenders for Object-Relational Systems 2000 VLDB 4.3622826e-05
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