PostgreSQL 7.4beta4 Documentation
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# 11.2. Index Types

PostgreSQL provides several index types: B-tree, R-tree, GiST, and Hash. Each index type is more appropriate for a particular query type because of the algorithm it uses. By default, the `CREATE INDEX` command will create a B-tree index, which fits the most common situations. In particular, the PostgreSQL query planner will consider using a B-tree index whenever an indexed column is involved in a comparison using one of these operators: <, <=, =, >=, >

The optimizer can also use a B-tree index for queries involving the pattern matching operators LIKE, ILIKE, ~, and ~*, if the pattern is anchored to the beginning of the string, e.g., col LIKE 'foo%' or col ~ '^foo', but not col LIKE '%bar'. However, if your server does not use the C locale you will need to create the index with a special operator class. See Section 11.6 below.

R-tree indexes are especially suited for spatial data. To create an R-tree index, use a command of the form

    CREATE INDEX name ON table USING RTREE (column);

The PostgreSQL query planner will consider using an R-tree index whenever an indexed column is involved in a comparison using one of these operators: <<, &<, &>, >>, @, ~=, && (Refer to Section 9.9 about the meaning of these operators.)

The query planner will consider using a hash index whenever an indexed column is involved in a comparison using the = operator. The following command is used to create a hash index:

    CREATE INDEX name ON table USING HASH (column);

> Note: Testing has shown PostgreSQL's hash indexes to be similar or slower than B-tree indexes, and the index size and build time for hash indexes is much worse. Hash indexes also suffer poor performance under high concurrency. For these reasons, hash index use is presently discouraged.

The B-tree index is an implementation of Lehman-Yao high-concurrency B-trees. The R-tree index method implements standard R-trees using Guttman's quadratic split algorithm. The hash index is an implementation of Litwin's linear hashing. We mention the algorithms used solely to indicate that all of these index methods are fully dynamic and do not have to be optimized periodically (as is the case with, for example, static hash methods).

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