Chroma vs Weaviate

Chroma: Open-source retrieval database for AI apps, from embedded Python to serverless Chroma Cloud. Weaviate: Open-source AI-native vector database with hybrid search, modules for embeddings and multi-tenancy.

key differences

Weaviate is built for larger datasets (≤ 1 PB) than Chroma (≤ 10 TB).
Transactions: Chroma offers limited ACID; Weaviate offers none.
Only Chroma has branching.
Only Weaviate has geospatial, compression, role-based access.
Chroma has a serverless option; Weaviate does not.
Chroma can run embedded in your application process.

choose chroma for

+Prototyping RAG in notebooks
+Embedded retrieval in Python apps
+Agent memory
+Serverless RAG backends

best at · Vector search, RAG, Search

choose weaviate for

+RAG over documents with hybrid retrieval
+Multi-tenant SaaS semantic search
+Product and content recommendation
+Agent memory stores

best at · Vector search, RAG, Search

ChromaOpen-source retrieval database for AI apps, from embedded Python to serverless Chroma Cloud.

WeaviateOpen-source AI-native vector database with hybrid search, modules for embeddings and multi-tenancy.

overview

Primary model

Vector

Also supports

Document, Search Engine

Type

Database engine

Status

Active

Developer

Chroma

Weaviate B.V.

First release

2023

2019

Latest version

1.5.9 (May 5, 2026)

1.40.2 (Oct 22, 2026)

License

Open source (permissive)Apache License 2.0

Open source (permissive)BSD-3-Clause (core); enterprise features under the Weaviate License

Free tier

✓

popularity

WhichDB Score

49.0

33.4

Rank

#29

#65

GitHub stars

29.6K

16.9K

Stack Overflow questions

266

160

scale & guarantees

Comfortable data size

Medium (≤ 10 TB)

Large (≤ 1 PB)

Horizontal scaling

Native

Multi-region

None

ACID

Limited

None

Consistency

Eventual

Tunable, Eventual

Schema

Schemaless

Flexible

Architecture

Embedded, Single node, Serverless, Client server

Distributed, Client server

deployment

Self-hosted

✓

Vendor-managed cloud

✓

Serverless

✓

—

Embedded

✓

—

Edge

—

Clouds

AWS

AWS, Google Cloud, Azure

capabilities

Transactions

—

Joins

—

Secondary indexes

✓

Full-text search

✓

Vector search

✓

Geospatial

—

✓

JSON

✓

Change data capture

—

Triggers

—

Stored procedures

—

Materialized views

—

TTL / expiry

—

Pub/Sub

—

Columnar storage

—

In-memory

—

Durable persistence

✓

Compression

—

✓

Encryption at rest

—

Role-based access

—

✓

Time travel

—

Branching

✓

—

Online schema changes

—

Streaming ingest

—

Offline sync

—

Runs in WebAssembly

—

interfaces

Query languages

Chroma API (where filters)

GraphQL, Weaviate query API

Client languages

Python, JavaScript, Rust

Python, TypeScript, Go, Java, C#

Best for

Vector search, RAG, Search, Embedded

Vector search, RAG, Search

Add more to this comparison Not sure either fits? Try smart match

Chroma vs Weaviate: FAQ

What is the difference between Chroma and Weaviate?

Chroma: Open-source retrieval database for AI apps, from embedded Python to serverless Chroma Cloud. Weaviate: Open-source AI-native vector database with hybrid search, modules for embeddings and multi-tenancy. Weaviate is built for larger datasets (≤ 1 PB) than Chroma (≤ 10 TB). Transactions: Chroma offers limited ACID; Weaviate offers none. Only Chroma has branching.

When should I choose Chroma over Weaviate?

Choose Chroma for prototyping RAG in notebooks, embedded retrieval in Python apps and agent memory. Choose Weaviate for RAG over documents with hybrid retrieval; multi-tenant SaaS semantic search; and product and content recommendation.

Is Chroma or Weaviate more popular?

Chroma ranks #29 on the WhichDB Score (49.0/100) and Weaviate ranks #65 (33.4/100). Popularity is not fit: check the requirements that matter for your project.

Are Chroma and Weaviate open source?

Yes. Chroma is open source. License: Apache License 2.0. Yes. Weaviate is open source. License: BSD-3-Clause (core); enterprise features under the Weaviate License.