Typesense
by Typesense, Inc. · Database
GPL-licensed in-memory search engine in C++ offering typo-tolerant instant search, faceting, vector and hybrid search, with Typesense Cloud hosting
Overview
Typesense is an open-source search engine written in C++ and released under the GNU GPL version 3. It keeps indexes in memory for low-latency, typo-tolerant instant search with faceting, filtering, sorting, geosearch, synonyms, curation rules and grouping, all driven by a simple REST API and official clients for JavaScript, Python, PHP, Ruby, Go, Java, Swift and .NET. Later releases added vector search, hybrid keyword-plus-semantic ranking with built-in or remote embedding models, conversational search backed by LLMs, and a multi-node clustering mode using Raft for high availability. Typesense Cloud is the managed service operated by the same company.
Typesense positions itself as an open-source alternative to hosted search APIs for websites and applications. Memory residency makes very large corpora expensive, the GPL may matter for teams embedding it in proprietary distributions, and aggregation-heavy analytics are outside its scope.
Capabilities
- In-memory typo-tolerant instant search
- Faceting, filtering, grouping and geosearch
- Vector and hybrid search with embedding models
- Conversational (RAG) search
- Raft-based multi-node high availability
- REST API with clients in eight languages
Typical workflows
- E-commerce or catalog search with facets
- Documentation and site search
- Hybrid semantic search for an application
Strengths
- Simple configuration and predictable relevance
- Clustering for availability
- Managed cloud from the project maintainers
Limitations
- Indexes must fit in memory
- GPL-3.0 license
- Not designed for analytics or log search
Prerequisites
- A server with enough RAM for the index, or Typesense Cloud
Who it is for
- Web and mobile developers adding search
Alternatives & comparison
- Elasticsearch
Distributed search and analytics engine on Apache Lucene with full-text, aggregations, vector search and ES|QL; triple-licensed AGPL, SSPL and Elastic License
MixedOpen source - Meilisearch
Rust search engine for application search-as-you-type with typo tolerance, faceting and hybrid semantic search; MIT core plus BSL enterprise parts
MixedOpen source - OpenSearch
Apache-2.0 search and analytics suite forked from Elasticsearch and Kibana, governed by the OpenSearch Software Foundation
Open sourceOpen source - Qdrant
Open-source vector search engine written in Rust with filterable HNSW indexes, sparse and multi-vector support, REST/gRPC APIs and a managed cloud
Open sourceOpen source
Sources & verification
Primary sources consulted for this record. Claims are tied to the fields each source supports; the automated link checker re-verifies every URL on a schedule.
- LicenseTypesense LICENSE.txt (GPLv3)checked Nov 1, 2026
https://github.com/typesense/typesense/blob/main/LICENSE.txt
Supports: license_spdx, source_model
- Official documentationchecked Nov 1, 2026
- Official sitechecked Nov 1, 2026
- Pricing pagechecked Nov 1, 2026
- Repositorychecked Nov 1, 2026
- Confidence
- High
- Reviewed
- Nov 1, 2026
- Links
- Verified · Nov 2, 2026
Spotted an error?
More in Vector databases
pgvector
Andrew Kane (pgvector project) · Vector databases
PostgreSQL extension adding vector types, distance operators and HNSW/IVFFlat indexes for similarity search inside the database
Weaviate
Weaviate B.V. · Vector databases
Open-source vector database in Go with pluggable vectorizer modules, hybrid BM25 and vector search, multi-tenancy and a managed cloud
Chroma
Chroma · Vector databases
Open-source embedding database with a minimal Python and JavaScript API, usable in-process, as a server or through Chroma Cloud
Pinecone
Pinecone Systems, Inc. · Vector databases
Fully managed, proprietary vector database service with serverless indexes, namespaces, metadata filtering and integrated embedding and reranking
Milvus
Zilliz / LF AI & Data Foundation · Vector databases
Open-source vector database from Zilliz with Lite, Standalone and Distributed deployments, many index types and GPU acceleration