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207 tools · 25 stacks

AI tools are all over the place. This is the full landscape — 207 tools across 17 categories, mapped and connected. Ready to narrow it down? Build your stack →

Team size

Budget

Use case

Stage

Cluster

Stack Layers
What are you building and how is it defined?
How do you write and ship code?
How does your AI think and act?
Which models and infrastructure power it?
How do you build, observe, and extend it?
These tools competes with
pgvector
vs
Pinecone

Choose pgvector when…

  • •You're already on PostgreSQL
  • •You want vector search without a separate database
  • •SQL queries combined with embedding search are needed

Choose Pinecone when…

  • •You want managed, scalable vector search
  • •You don't want to run infra and need SLAs
  • •High availability and zero ops for vector DB matter
Field
pgvector
Pinecone
Category
LLM Infrastructure
LLM Infrastructure
Type
OSS
SaaS
Free Tier
✓ Yes
✓ Yes
Plans
—
Standard: Usage-based
Stars
⭐ 13,000
—
Health
●75 — Active
—
Trajectory
— not enough data
— not enough data
Synced
today
—

pgvector

Adds vector similarity search to PostgreSQL. Perfect for teams already on Postgres who don't want to manage a separate vector DB.

Pinecone

Fully managed vector database with serverless indexes. No ops overhead. The go-to managed option for production RAG.

pgvector Website ↗GitHub ↗
Pinecone Website ↗

Shared Connections (4)

LangChainLlamaIndexQdrantMilvus

Only pgvector (3)

LangGraphPineconeRedis Vector

Only Pinecone (5)

HaystackWeaviateChromapgvectorturbopuffer
See full comparison in Explore →