CODS: Evolving Data Efficiently and Scalably in Column Oriented Databases
Summary: CODS enables data-level evolution in columnar DBs, updating data to a new schema without materializing results or unnecessary compression/decompression. It achieves orders-of-magnitude faster evolution than query-level approaches in commercial/open-source RDBMSs and scales to large data warehouses. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Ziyang Liu
- 2. Sivaramakrishnan Natarajan
- 3. Bin He
- 4. Hui-I Hsiao
- 5. Yi Chen
Incoming Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 21 | C-Store: A Column-oriented DBMS | 2005 | VLDB | 0.00086087497 |
| 131 | Integrating Compression and Execution in Column-Oriented Database Systems | 2006 | SIGMOD | 0.0004370331 |
| 1,677 | Graceful Database Schema Evolution: the PRISM Workbench | 2008 | VLDB | 0.00010939366 |
| 4,520 | Managing and Querying Transaction-time Databases under Schema Evolution | 2008 | VLDB | 6.1170427e-05 |
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