Cost Model Development for a Main Memory Database System

Main-memory database management systems (MM-DBMS’s) are at the heart of RTDB’s, and research in MM-DBMS’s has been active since the mid-eighties [8, 7, 1, 9]. Recently the interest has taken on a new urgency as inexpensive memory and 64-bit addressing are becoming reality. Several fairly complete systems [12, 14, 3] have been developed in the last few years, and recent investigations have taken a fresh look at a variety of issues in the context of main-memory: recovery [15, 19, 20, 16], indexing [2, 23], parallelism [3], and concurrency control [11], for example. However, the issue of query optimization has largely been neglected, partly because many of the applications suited to main-memory systems (e.g., telecom switching and financial trading) use only simple queries requiring, say, a hash lookup on a single table. There are, however, a few applications that require complex queries over memory-resident data. These include financial analysis, and fraud detection in the context of telecommunication. Moreover, we consider main-memory databases to be a “disruptive technology” [5] and so we anticipate that as the technology becomes more widely adopted, MM-DBMS’s will be used in increasingly general-purpose situations, which will require query optimization. Indeed, the recent announcement that Oracle will be including a copy of an in-memory database with each Oracle7 system [22] goes some way toward justifying this belief. Similarly, the emerging popularity of object-oriented DBMS’s, which is partly due to their high performance, is to a great extent attributable to the memory residence of the data.