LightDB provides several index types: B-tree, Hash, GiST and GIN. Each index type uses a different algorithm that is best suited to different types of queries. By default, the CREATE INDEX command creates B-tree indexes, which fit the most common situations.

B-trees can handle equality and range queries on data that can be sorted into some ordering. In particular, the LightDB query planner will consider using a B-tree index whenever an indexed column is involved in a comparison using one of these operators:

Constructs equivalent to combinations of these operators, such as BETWEEN and IN, can also be implemented with a B-tree index search. Also, an IS NULL or IS NOT NULL condition on an index column can be used with a B-tree index.

The optimizer can also use a B-tree index for queries involving the pattern matching operators LIKE and ~ if the pattern is a constant and is anchored to the beginning of the string — for example, col LIKE 'foo%' or col ~ '^foo', but not col LIKE '%bar'. However, if your database does not use the C locale you will need to create the index with a special operator class to support indexing of pattern-matching queries; see Section 11.10 below. It is also possible to use B-tree indexes for ILIKE and ~*, but only if the pattern starts with non-alphabetic characters, i.e., characters that are not affected by upper/lower case conversion.

B-tree indexes can also be used to retrieve data in sorted order. This is not always faster than a simple scan and sort, but it is often helpful.

Hash indexes can only handle simple equality comparisons. 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);

GiST indexes are not a single kind of index, but rather an infrastructure within which many different indexing strategies can be implemented. Accordingly, the particular operators with which a GiST index can be used vary depending on the indexing strategy (the operator class). As an example, the standard distribution of LightDB includes GiST operator classes for several two-dimensional geometric data types, which support indexed queries using these operators:

(See Section 9.11 for the meaning of these operators.) The GiST operator classes included in the standard distribution are documented in Table 59.1. Many other GiST operator classes are available in the contrib collection or as separate projects. For more information see Chapter 59.

GIN indexes are “inverted indexes” which are appropriate for data values that contain multiple component values, such as arrays. An inverted index contains a separate entry for each component value, and can efficiently handle queries that test for the presence of specific component values.

GIN can support many different user-defined indexing strategies, and the particular operators with which a GIN index can be used vary depending on the indexing strategy. As an example, the standard distribution of LightDB includes a GIN operator class for arrays, which supports indexed queries using these operators:

(See Section 9.19 for the meaning of these operators.) The GIN operator classes included in the standard distribution are documented in Table 60.1. Many other GIN operator classes are available in the contrib collection or as separate projects. For more information see Chapter 60.