Index › IT › Products › ChromaDB · November 2026 Edition
Vector databases · Named, not ranked

ChromaDB

ChromaDB is a vector database for general users and power users, with a collection of small guides and recipes to help them get started · chromadb.dev ↗

–Too few to rank
9/14Models named it
1First choices
8Warnings
November 2026 Edition · all company sizes counted.
Ranked inVector databases #10 mid-market
What AI models recommend

Named, too few times to rank.

A product needs 10 labels in a category before a share is stated. ChromaDB has 5.

Why models recommend it

“For prototyping or very small projects; runs locally, zero setup, good for development.”GLM 4.7 FlashX · Budget-constrained question · alternative
“Easiest to Get Started ... Trade-off: Not production-scalable past ~1M vectors”MiniMax M2.5 · Budget-constrained question · alternative
“If you are building an MVP or running local code: Use ChromaDB.”Gemini 3.5 Flash · Comparative question · alternative
“If you are rapidly prototyping in Python/JS: ChromaDB”Gemini 3.5 Flash · Budget-constrained question · alternative

What gives them pause

No model argued against it.

Also on the shortlist

The products named in the same answers as ChromaDB, over the 16 answers that named it, and how often each was the first choice instead.

A side-by-side page exists where both products are among a category's top eight.

At a glance

Stated on ChromaDB's own site, not checked by Gane.

For
For General Users; For Power Users
Integrations
3
Visit chromadb.dev ↗

How this is measured

Fourteen AI models from 12 labs are asked the same buying questions six ways, for three company sizes. Standings refresh every edition.

Gane sells AI visibility software. No company can pay to change a result.

Read the method →

Sources returned with these answers

The sites and pages the answers that named ChromaDB came back with. A fact about retrieval, not a cause of the answer.

Fourteen of the fourteen models returned a source list in this edition: five return the pages they cited and nine the search results they consulted. These counts come from 13 of the 16 answers that named ChromaDB and are not a share of its labels.

By model

How each model answered on ChromaDB across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ModelFirst choiceAlternativeMentionWarningLabels
Claude Haiku 4.500101
GPT-5.4 mini00000
Gemini 3.5 Flash02002
Perplexity Sonar00000
Grok 4.2000000
Mistral Small00000
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash00000
Kimi K200000
GLM 4.7 FlashX01001
MiniMax M2.501001
GPT-6 Luna00000
Muse Glimmer 30B00000