Chroma: Vector Databases

Founded 2022|San Francisco, CA|11-50 people|Open Source

What is Chroma?

Chroma is an open-source embedding database designed for simplicity and developer experience, licensed under Apache 2.0. It provides a lightweight, easy-to-use API for storing, querying, and filtering embeddings locally or in the cloud.

Chroma is the default vector store in many LLM frameworks like LangChain and LlamaIndex, making it extremely popular for prototyping and building RAG applications quickly. The managed Chroma Cloud service offers serverless deployment with usage-based pricing, while the self-hosted version runs on a single node at no cost.

The company achieved SOC 2 Type II compliance for enterprise deployments and offers Chroma Cloud with features including BYOC in your VPC, multi-cloud/multi-region replication, and point-in-time recovery. Chroma is rated 4.2/5 on G2.

Key features

Core capabilities this platform advertises.

Lightweight embedded vector database
Python-native API
Runs in-process without a server
Simple document and query interface
Open-source and free

Strengths and tradeoffs

What this tool does well, and the limitations to keep in mind.

Pros

Extremely simple to set up and beginner-friendly
Apache 2.0 open source with free self-hosting
Default vector store in LangChain and LlamaIndex frameworks
Cloud reads are effectively free ($0.0075/TiB)
SOC 2 Type II compliance for enterprise deployments

Cons

Single-node architecture limits scalability for self-hosted deployments
Performance may not match Pinecone at very large scale
Limited advanced documentation for complex use cases
Enterprise features like SSO are less mature than competitors

Plans & pricing

What's included in each plan, and how the tiers compare.

Self-Hosted (Open Source)

Free

Apache 2.0 license
Local deployment
Docker support
Single-node architecture

Cloud Starter

$0 + $5 free credits

Usage-based

Usage-based pricing
$0.33/GB/month storage
$2.50/GB data ingestion
Near-free reads ($0.0075/TiB)

Cloud Pro

Usage-based with volume discounts

Higher limits
Priority support
Volume-based discounts

Enterprise

Custom

Contact sales for a quote

SOC 2 Type II
BYOC in your VPC
Custom SLAs
24/7 support

View official pricing page

Common use cases

Python developers who want a simple, embedded vector database for prototyping

Local development and prototyping
Small to medium RAG applications
Embedded vector search in Python apps
Research and experimentation
Serverless and edge deployments

Using Chroma with Respan

Respan integrates with Chroma to provide observability into embedding quality and retrieval performance. Teams can monitor how Chroma-powered RAG applications perform in production and identify opportunities to improve retrieval accuracy.

Monitor Chroma query performance and retrieval relevance
Evaluate embedding quality across different models
Track storage costs and query patterns over time
Identify retrieval gaps in RAG application workflows

Run Chroma in production with Respan

10KFree traces/mo

1,000+Models

5 minSetup

Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.

Try Respan free

Best Chroma alternatives & competitors

Top companies in Vector Databases you can use instead of Chroma.

Milvus

Billion-scale vector search