product
Data quality: Editorially ReviewedRetrieval & data layer
Vector Databases
Software & technology
Workflow orchestration
Self-hosted / on-premises
Freemium
SaaS (vendor-hosted)
Retrieval & semantic search
Timescale Vector
Vector Databases
Overview
Timescale Vector is a PostgreSQL-based vector database that enables AI applications to store and query vector embeddings at scale. It provides specialized indexing for time-series and vector data, supports hybrid search, and integrates with the pgvector extension. Timescale Vector is designed for applications that need to combine time-series data with vector similarity search.
- Pricing model
- Freemium
- Deployment
- SaaS (vendor-hosted), Self-hosted / on-premises
- Regions served
- Global
- Categories
- Retrieval & data layer, Vector Databases, Software & technology, Workflow orchestration, Self-hosted / on-premises, Freemium, SaaS (vendor-hosted), Retrieval & semantic search
- Last updated
- 2 October 2026
- Published
- 2 October 2026
Use cases
Workflow orchestration
Deployment options
SaaS (vendor-hosted)
Self-hosted / on-premises
Data sources & provenance
Where this information came from, how it was checked and when it was last looked at. “Last updated” records a change to the record — it does not mean the record was verified.
- Data quality
- Data quality: Editorially Reviewed
- Primary source
- timescale.com
- Sources cited
- 2
- Last reviewed
- 28 September 2026
- Last updated
- 2 October 2026
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Anyone can suggest a correction — you don't need an account. An editor checks every suggestion against the sources before the record changes.