Implementation techniques for main memory database systems

  • Authors:

  • David J DeWitt;Randy H Katz;Frank Olken;Leonard D Shapiro;Michael R Stonebraker;David A. Wood

  • Affiliations:

  • University of Wisconsin;University of California at Berkeley;Lawrence Berkeley Laboratory;North Dakota State University;University of California at Berkeley;University of California at Berkeley

  • Venue:
  • SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
  • Year:
  • 1984

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Abstract

With the availability of very large, relatively inexpensive main memories, 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 advantageous for large memory situations