TOML

Database Index Types - TOML

Database indexes are data structures used to speed up data retrieval. Various types exist depending on the use case, including B-Tree indexes, Hash indexes, and Bitmap indexes, each optimized for specific query patterns and data characteristics. Selecting the appropriate index is a crucial element in database performance optimization.

database index B-Tree Hash Bitmap SQL performance optimization

[[items]]
code = "1"
slug = "b-tree-index"
name = "B-Tree Index"
description = "The most commonly used balanced tree structure index."
category = "General-purpose Index"
supportedDatabases = "[\"MySQL\",\"PostgreSQL\",\"Oracle\",\"SQL Server\",\"MongoDB\"]"
useCases = "[\"Equality searches\",\"Range queries\",\"Sorting operations\",\"Primary keys\",\"Foreign keys\"]"

[[items]]
code = "2"
slug = "hash-index"
name = "Hash Index"
description = "An index providing constant-time access using hash functions."
category = "Key-value Index"
supportedDatabases = "[\"Redis\",\"MySQL (MEMORY)\",\"PostgreSQL\",\"Some NoSQL databases\"]"
useCases = "[\"Equality searches\",\"Point lookups\",\"Transaction processing\",\"Key-value access\"]"

[[items]]
code = "3"
slug = "bitmap-index"
name = "Bitmap Index"
description = "An index using bit arrays optimized for low-cardinality columns."
category = "Analytical Index"
supportedDatabases = "[\"Oracle\",\"PostgreSQL (extensions)\",\"Data warehouse systems\"]"
useCases = "[\"Low-cardinality columns\",\"Data warehousing\",\"Complex filtering\",\"Read-heavy environments\"]"

[[items]]
code = "4"
slug = "full-text-index"
name = "Full-Text Index"
description = "An index specialized for searching unstructured text data."
category = "Text Search Index"
supportedDatabases = "[\"MySQL\",\"PostgreSQL\",\"SQL Server\",\"Elasticsearch\"]"
useCases = "[\"Full-text search\",\"Partial match search\",\"Similar word search\",\"Document search\"]"

[[items]]
code = "5"
slug = "vector-index"
name = "Vector Index"
description = "An index specialized for similarity search of high-dimensional vectors."
category = "AI/ML Index"
supportedDatabases = "[\"PostgreSQL (pgvector)\",\"Pinecone\",\"Milvus\",\"Weaviate\"]"
useCases = "[\"Similarity search\",\"Image search\",\"Recommendation systems\",\"Semantic search\"]"

[[items]]
code = "6"
slug = "spatial-index"
name = "Spatial Index"
description = "An index specialized for searching geospatial data."
category = "Geospatial Index"
supportedDatabases = "[\"PostgreSQL (PostGIS)\",\"MySQL\",\"Oracle Spatial\",\"MongoDB\"]"
useCases = "[\"Neighbor search\",\"Range search\",\"Distance calculation\",\"Geographic information search\"]"