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Most pmv~ous work m the ama of mam memory database systems has focused on the problem of developing query processmg techmoues that work well wnh a very large buffer pool In thus paper, -we address query processmg issues for memoryresrdent relauonal databases, an envuonment wrth a very dtfferent set of costs and pnonues We present an arclutectum for a main memory DBMS, discussing the ways m whtch a memory resident database differs from a disk-based database We then address the problem of processmg relauonal quenes 1n bus archttecture, cons1denng altema-t1ve algonthms for seleetron, pmpecuon, and Join opemnons and studying then performance We show that a new mdex structure, the T Tree, works well for selectton and JOM processing in memory restdent databases We also show that bashmg methods work well for processmg pro~cttons and JOUIS. and that an old Join method, sort-merge, shll has a place m mam memory

Most previous work in the area of main memory database systems has focused on the problem of developing query processing techniques that work well with a very large buffer pool. In this paper, we address query processing issues for memory resident relational databases, an environment with a very different set of costs and priorities. We present an architecture for a main memory DBMS, discussing the ways in which a memory resident database differs from a disk-based database. We then address the problem of processing relational queries in this architecture, considering alternative algorithms for selection, projection, and join operations and studying their performance. We show that a new index structure, the T Tree, works well for selection and join processing in memory resident databases. We also show that hashing methods work well for processing projections and joins, and that an old join method, sort-merge, still has a place in main memory.

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