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The TEXTURE Benchmark: Measuring Performance of Text Queries on a Relational DBMS

Summary: TEXTURE measures efficiency of text processing within relational workloads, emphasizing ranking and rich text-relational integration. Synthetic generator to scale text fields mirroring a seed collection, with performance across three commercial DBMSs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9313
Venue
VLDB
Year
2005
Pagerank
4.9577992e-05
Overall Rank
6,697 | 53.42%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
2,994 Data Generation for Application-Specific Benchmarking 2011 VLDB 7.761114e-05
3,252 Auto-Suggest: Learning-to-Recommend Data Preparation Steps Using Data Science Notebooks 2020 SIGMOD 7.3178277e-05
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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.

Rank Cited Paper Year Venue Pagerank
145 Quickly Generating Billion-Record Synthetic Databases 1994 SIGMOD 0.0004138408
638 On B-tree Indices for Skewed Distributions 1992 VLDB 0.00018798677
1,154 Fast Incremental Indexing for Full-Text Information Retrieval 1994 VLDB 0.00013642184
3,079 Extended User-Defined Indexing with Application to Textual Databases 1988 VLDB 7.6037529e-05
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