Chroma vs turbopuffer

Two sides of the vector database decision: embedded / local-first and managed vector store. When each fits, what it costs, who moves from one to the other, and what makers who chose it say.

Ask your AI about this, with this page as the source:ChatGPT ↗Claude ↗Perplexity ↗

Which fits you

Choose Chroma if
  • You're prototyping retrieval on your laptop, or want vectors in files with no server

Use it whenYou're still figuring out whether retrieval works for your use case.

Trade-offFor production you either run its server yourself or move to Chroma Cloud.

Choose turbopuffer if
  • You want a hosted index with nothing to operate

Use it whenYou have many separate namespaces, such as one index per customer.

Trade-offNo free tier (paid plans have a monthly minimum), and it's cloud-only.

At a glance

Chromaturbopuffer
Used by13 makers' products · 69 open-source projects8 makers' products · 7 open-source projects
Cost at default usagevectors stored 1 million vectors, queries 1 million queries, vectors written or updated 500k writes$51/mo Starter$21/mo Launch
Downloads236.5k/wk−12% vs npm1.1M/wk3.9× vs npm
PricingFree and open source to self-host (Apache-2.0); Chroma Cloud is usage-based with free starting credits. · paid from Usage-basedUsage-based tiers with a monthly minimum; higher tiers add SSO, audit logs, and enterprise/BYOC deployments. · paid from $16/mo minimum usage
Free tierYesNo
Open sourceYes · self-hostableNo
Incidents, 90 daysfrom its status pageno public status feed4 (4 major)

Cost as you grow

At 100k vectors Chroma costs less ($1.32 vs $17); from about 1M vectors turbopuffer does ($21 vs $51). They're different kinds of tool — embedded / local-first and managed vector store — so the prices don't buy the same thing.

$0$10,000$50,000$100,000$200,0000.10.5151050100
turbopufferChromax: vectors stored (1,536 dimensions, about 6 gb per million) (million vectors), other usage scaled with it · cheapest usable plan at each point, list prices · try your own numbers
The numbers, plan by plan
Vectors stored (1,536 dimensions, about 6 GB per million)Chromaturbopuffer
0.1$1.32 Starter$17 Launch
0.5$15 Starter$19 Launch
1$51 Starter$21 Launch
5$1,093 Starter$179 Launch
10$4,281 Starter$430 Launch
50$105,226 Starter$3,173 Launch
100$419,999 Starter$7,576 Scale

From each vendor's pricing page: Chroma, turbopuffer.

What makers say

Makers on using it for vector database, from Product Hunt and Starter Story interviews, each linked to the source. Products with a page of their own and fuller notes first.

On Chroma
Chroma makes it super easy to manage embeddings for AI apps. We love the open-source focus and how quickly it integrates into RAG pipelines.
VoltAgent, the makerSep 2026 ↗
Jeff (the founder) is incredible - super knowledgeable and I'm super bullish on the direction of the product. Let's go!
Clarm, the makerSep 2026 ↗
Powered memory storage with a dead-simple, blazing-fast open-source vector DB. Far easier to self-host than alternatives.
Convo, the makerSep 2026 ↗
2 more on the Chroma page →
On turbopuffer

No maker quote about turbopuffer for vector database yet.

Loved and watch-outs

Themes that recur in makers' words and Hacker News comments, each linked to what it summarises.

Chroma
Most loved
  • Open source and easy to self-host, with a simple API that gets embeddings stored quickly. PHHN
  • Full-text and regex search sit alongside vector search, and collection forking suits changing code. trychroma.comHNHN 2HN 3
  • Plugs quickly into RAG pipelines and local-first tools built on LangChain or Ollama. PHHNHN 2HN 3
Watch-outs
  • Its feature set is narrower than Milvus or Weaviate, lacking vector quantization and some index options. HNHN 2
On Product Hunt: 5.0★, 10 reviews
turbopuffer
Most loved
Watch-outs
  • There is no offline local emulator, so development and CI must hit the hosted service. HNHN 2HN 3
  • Its paid-only pricing floor is steep for small projects, which often stay on pgvector instead. HNHN 2

Who uses each

What makers pair each with

pgvectorInside your databaseApps already on Postgres that want vector search in the same database, joined with normal tables.
PineconeManaged vector storeA fully hosted index with nothing to operate, sized by usage.vs Chroma →vs turbopuffer →
QdrantOpen-source vector storeHeavy metadata filtering alongside vector search, self-hosted from one binary or on its managed cloud.vs Chroma →vs turbopuffer →
WeaviateOpen-source vector storeHybrid search that mixes keyword and vector results, with built-in modules that can create embeddings for you.