Which is better: pgvector or Pinecone?

There's no single 'better' — they target different points in the Vector Databases space. Pick by your install constraints (license, MCP-native vs generic, hosting model) and the tag overlap above.

Can I use both pgvector and Pinecone?

Usually yes. Both are vector databases — they're not mutually exclusive in most stacks. Many teams run both during evaluation and standardize on one after a sprint.

Where do the recommendations come from?

ClaudSkills Arcade is an open community catalog. Discovery is mined from 7 public sources daily. Ranking is content-derived — no paid placements.

pgvector vs Pinecone — Vector Databases compared on ClaudSkills Arcade

pgvector

Vector similarity search as a PostgreSQL extension. The 'boring tech' pick for RAG.

License: PostgreSQL
Install: external link
Website: https://github.com/pgvector/pgvector
GitHub: https://github.com/pgvector/pgvector

View pgvector →

https://github.com/pgvector/pgvector#installation

Pinecone

Managed serverless vector DB — fast, scalable, and category-leader for production RAG.

License: proprietary
Install: pip package
Website: https://www.pinecone.io
GitHub: https://github.com/pinecone-io

View Pinecone →

pip install pinecone-client

Shared tags

rag vector-db

Only in pgvector

extension open-source postgres

Only in Pinecone

managed serverless

When to reach for which

pgvector — Vector similarity search as a PostgreSQL extension. The 'boring tech' pick for RAG.

Pinecone — Managed serverless vector DB — fast, scalable, and category-leader for production RAG.

Both sit in the Vector Databases category — they're substitutes, not complements. Pick by your install constraint (MCP-native, license, hosting model) and which tag overlap matters most to your stack.

More Vector Databases comparisons

See all comparisons →

pgvectorvsPinecone