It is our great pleasure to welcome you to the 35th ACM SIGMOD Conference. This year's conference took place in beautiful Providence, capital of Rhode Island, the Ocean State, and home to renowned schools and top-flight chefs.
SIGMOD 2009 continues its tradition as a premier forum for the presentation of research results, industry developments, tutorials, and demos in the general area of data management. In addition, SIGMOD 2009 hosts a variety of collocated workshops, the new researcher symposium, and the ACM SIGMOD programming contest which was held for the first time in 2009.
The call for research papers attracted 430 submissions of which 397 were peer-reviewed. (30 submissions did not comply with SIGMOD's double-blind reviewing policy; a few submissions did not comply with the length constraints or were withdrawn by the authors.) Of the 397 reviewed submissions, 63 papers were accepted for presentation at the conference. Furthermore, five tutorials, eighteen industry papers, and thirty-two demos were invited for presentation. The conference highlights include two keynotes, one by Hasso Plattner and one by Martin Wattenberg and Fernanda Viegas. Furthermore, the conference features five additional invited talks in the areas of human-computer interaction and systems, and a special session to celebrate the 40 th anniversary of the invention of the relational data model.
A common database approach for OLTP and OLAP using an in-memory column database
When SQL and the relational data model were introduced 25 years ago as a general data management concept, enterprise software migrated quickly to this new technology. It is fair to say that SQL and the various implementations of RDBMSs became the ...
Transforming data access through public visualization
Data visualization has historically been accessible only to the elite in academia, business, and government. It was "serious" technology, created by experts for experts. In recent years, however, web-based visualizations--ranging from political art ...
Cited By
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Liu Y, Zeng X and Zhang H (2024). LeCo: Lightweight Compression via Learning Serial Correlations, Proceedings of the ACM on Management of Data, 10.1145/3639320, 2:1, (1-28), Online publication date: 12-Mar-2024.
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Chen Y and Chen S (2024). Cabin: A Compressed Adaptive Binned Scan Index, Proceedings of the ACM on Management of Data, 10.1145/3639312, 2:1, (1-26), Online publication date: 12-Mar-2024.
Recommendations
Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
SIGMOD '19 | 430 | 88 | 20% |
SIGMOD '18 | 461 | 90 | 20% |
SIGMOD '15 | 415 | 106 | 26% |
SIGMOD '14 | 421 | 107 | 25% |
SIGMOD '13 | 372 | 76 | 20% |
SIGMOD '12 | 289 | 48 | 17% |
SIGMOD '03 | 342 | 53 | 15% |
SIGMOD '02 | 240 | 42 | 18% |
SIGMOD '01 | 293 | 44 | 15% |
SIGMOD '00 | 248 | 42 | 17% |
SIGMOD '97 | 202 | 42 | 21% |
SIGMOD '96 | 290 | 47 | 16% |
Overall | 4,003 | 785 | 20% |