**Description:**
This commit adds a vector store for the Postgres-based vector database
(`TimescaleVector`).
Timescale Vector(https://www.timescale.com/ai) is PostgreSQL++ for AI
applications. It enables you to efficiently store and query billions of
vector embeddings in `PostgreSQL`:
- Enhances `pgvector` with faster and more accurate similarity search on
1B+ vectors via DiskANN inspired indexing algorithm.
- Enables fast time-based vector search via automatic time-based
partitioning and indexing.
- Provides a familiar SQL interface for querying vector embeddings and
relational data.
Timescale Vector scales with you from POC to production:
- Simplifies operations by enabling you to store relational metadata,
vector embeddings, and time-series data in a single database.
- Benefits from rock-solid PostgreSQL foundation with enterprise-grade
feature liked streaming backups and replication, high-availability and
row-level security.
- Enables a worry-free experience with enterprise-grade security and
compliance.
Timescale Vector is available on Timescale, the cloud PostgreSQL
platform. (There is no self-hosted version at this time.) LangChain
users get a 90-day free trial for Timescale Vector.
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Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Avthar Sewrathan <avthar@timescale.com>
