Implementation Techniques for Main Memory Database Systems.

David J. DeWitt, Randy H. Katz, Frank Olken, Leonard D. Shapiro, Michael Stonebraker, David A. Wood: Implementation Techniques for Main Memory Database Systems. SIGMOD Conference 1984: 1-8

@inproceedings{DBLP:conf/sigmod/DeWittKOSSW84,
  author    = {David J. DeWitt and
               Randy H. Katz and
               Frank Olken and
               Leonard D. Shapiro and
               Michael Stonebraker and
               David A. Wood},
  editor    = {Beatrice Yormark},
  title     = {Implementation Techniques for Main Memory Database Systems},
  booktitle = {SIGMOD'84, Proceedings of Annual Meeting, Boston, Massachusetts,
               June 18-21, 1984},
  publisher = {ACM Press},
  year      = {1984},
  pages     = {1-8},
  ee        = {http://doi.acm.org/10.1145/602259.602261, db/conf/sigmod/DeWittKOSSW84.html},
  crossref  = {DBLP:conf/sigmod/84},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

With the availability of very large, relatively inexpensive main memorry, it is becoming possible keep large databases resident in main memory. In this paper we consider the changes necessary to permit a relational database system to take advantage of large amounts of main memory. We evaluate AVL vs B+-tree access methods for main memory databases, hash-based query processing strategies vs sort-merge, and study recovery issues when most or all of the database fits in main memory. As expected, B+-trees are the preferred storage mechanism unless more than 80-90% of the database fits in main memory. A somewhat surprising result is that hash based query processing strategies are an advantageous for large memory situations.

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References

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