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pgvector vs Chroma(2026)

pgvector is better for teams that need no new infrastructure. Chroma is the stronger choice if easiest to get started. pgvector is open-source (from $0) and Chroma is open-source (from $0).

Full feature breakdown, pricing details, and pros & cons below.

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pgvector logo

pgvector

open-source

pgvector adds vector similarity search directly to PostgreSQL — store embeddings alongside your relational data and run nearest-neighbor searches with standard SQL.

Starting at $0

Visit pgvector
Chroma logo

Chroma

open-source

Chroma is the leading open-source embedding database for LLM applications. With a simple Python/JavaScript API, it is the easiest way to add memory and context to AI apps.

Starting at $0

Visit Chroma

How Do pgvector and Chroma Compare on Features?

FeaturepgvectorChroma
Pricing modelopen-sourceopen-source
Starting price$0$0
PostgreSQL extension
L2/inner product/cosine distance
IVFFLAT indexing
HNSW indexing
Standard SQL
Works with Supabase/RDS
Exact + ANN search
Open source (Apache 2.0)
In-memory or persistent
Python and JS SDKs
Multi-modal embeddings
Filtering
LangChain/LlamaIndex integration
Simple API

pgvector Pros and Cons vs Chroma

p

pgvector

+No new infrastructure
+Works with existing Postgres
+SQL interface
+Supabase has it built-in
Not as fast as dedicated vector DBs at scale
Limited to Postgres ecosystem
Less filtering flexibility
C

Chroma

+Easiest to get started
+Perfect for prototyping
+Great LLM framework integrations
+Free forever
Less suited for production scale
No managed cloud (Chroma Cloud in beta)
Limited enterprise features

Should You Use pgvector or Chroma?

Choose pgvector if…

  • No new infrastructure
  • Works with existing Postgres
  • SQL interface

Choose Chroma if…

  • Easiest to get started
  • Perfect for prototyping
  • Great LLM framework integrations

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