DB2 Design Advisor: Integrated Automatic Physical Database Design
By D. Zilio, Jun Rao, S. Lightstone, G. Lohman, Adam J. Storm, Christian Garcia-Arellano, Scott Fadden. Very Large Data Bases Conference, 2004
383 citations recorded by the source corpus.
Subfields: Hardware and Architecture
View Paper: https://www.semanticscholar.org/paper/bfdefd687a5d129657e75c1bbb44925d54fc9e0f
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In Hardware and Architecture
Citations in the corpus
- Self-Tuning Database Systems: A Decade of Progress (2007, methodology): “Also, unlike [69] it does not propose candidates that are syntactically valid but might not be exploited by the optimizer.”
- To Tune or not to Tune? A Lightweight Physical Design Alerter (2006, methodology): “Most vendors nowadays offer automated tools to tune the physical design of a database as part of their products (e.g., [1, 8, 14]).”
- Skew-aware automatic database partitioning in shared-nothing, parallel OLTP systems (2012, neutral): “Most notable are the advancements from two commercial database vendors: Microsoft’s SQL Server AutoAdmin [12, 11, 3, 5, 32] and IBM’s DB2 Database Advisor [39, 50].”
- An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning (2019, methodology): “Major database vendors offer tools for automating database physical design [6, 9, 53, 57], and they focused on index optimizations, materialized views and partitions [1–3, 8, 23, 28, 36].”