# blevesearch/bleve

A modern text/numeric/geo-spatial/vector indexing library for go

Repository: https://github.com/blevesearch/bleve
Canonical: https://ross.abutalabs.com/products/bleve
Language: Go
License: Apache-2.0
License Family: permissive
Last push: 2026-08-26T13:29:38+00:00

## Health v2 (maintenance only)
Score: 95/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 87, longevity 100
- inputs: {"age_days": 4521, "days_push": 7, "days_rel": 9, "gap_med": 41, "n_releases_24m": 12}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 11187, forks 712 (observed 2026-08-28T04:10:46.333855+00:00)

## What it is
Bleve is a full-text indexing and search library for Go supporting text, numeric, datetime, geo-spatial, and vector fields. It provides rich query types, BM25/TF-IDF scoring, faceting, and hybrid exact-plus-semantic search embedded in your application.

## Use cases
- add full-text search to a Go application
- index JSON documents and query them with match or phrase queries
- search documents by geographic location or shape
- run k-nearest-neighbor vector search alongside keyword search
- build faceted search with terms and range aggregations
- implement fuzzy and wildcard search over structured data

## When to choose
- you need an embedded search engine in Go without running a separate search server
- you need combined text, numeric, geo, and vector indexing in one library
- you want hybrid keyword and semantic search with rank fusion

## When to avoid
- you need a distributed, horizontally scalable search cluster
- your stack is not Go and you prefer a standalone engine like Elasticsearch
- you only need simple key-value lookups without relevance ranking

## Facets
- artifact type: library
- maturity: active
- function: search-engine, database, vector-database
- domain: databases, developer-tools
- platform: go, cross-platform
- tags: full-text-search, indexing, geo-search, vector-search, bm25, hybrid-search, embedded, search

## Member repositories
- blevesearch/bleve (main) score 95

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:46.333855+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:16:42.509133+00:00, confidence not recorded.
  - readme: https://github.com/blevesearch/bleve (fetched 2026-08-28T04:10:46.333855+00:00, sha 9d69c5520682)
- Data as of 2026-08-30T08:39:29.467469+00:00.