Pgvector

pgvector is an open-source PostgreSQL extension that adds vector data types and similarity search capabilities to PostgreSQL. It enables applications to store, index, and search AI-generated embeddings directly within PostgreSQL, making it useful for semantic search, recommendation systems, AI applications, and Retrieval-Augmented Generation (RAG) workflows.

• Store high-dimensional AI and machine learning embeddings directly in PostgreSQL databases.
• Perform vector similarity searches using Euclidean distance, inner product, and cosine distance.
• Support efficient approximate nearest-neighbor searches using HNSW and IVFFlat indexes.
• Keep vector embeddings, relational data, metadata, and application data together in a single PostgreSQL database.
• Support AI applications such as semantic search, recommendation systems, document retrieval, and RAG pipelines.
• Integrate with popular AI and machine learning frameworks and embedding-generation models.

pgvector Usage:

$ sudo su
$ apt update
$ cd /opt/pgvector
$ sudo -u postgres psql

# Enable pgvector:
postgres=# CREATE EXTENSION vector;

# Check installed pgvector version:
postgres=# SELECT extversion FROM pg_extension WHERE extname = 'vector';

# Check PostgreSQL version:
postgres=# SELECT version();

  

Disclaimer: pgvector is provided "as is," without any warranty, express or implied. Users utilize this software at their own risk. pgvector is an open-source project, and its use is subject to the applicable project license and dependencies. It is not affiliated with, endorsed by, or sponsored by kCloudHubs. The developers and contributors of pgvector are not responsible for any damages, losses, or consequences resulting from the use of this software.