Databases · head to head
Chroma vs Zilliz
Chroma
Databases
Apache 2.0 vector and full-text search engine that runs as an embedded library, a single server or a distributed cloud service.
- From
- Free
- Rated
- -
Zilliz
Databases
Managed vector database and vector lakebase for AI applications
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Chroma on a single node, available memory sets a hard upper bound on collection size, roughly 245,000 records per gigabyte of RAM at 1024 dimensions, so capacity planning is a memory purchase and the ceiling arrives without warning.; Zilliz pricing structure not publicly disclosed, requires sales contact
- They diverge on capability: Chroma covers Embedded mode, Zilliz covers Vector indexing.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Chroma and Zilliz actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Chroma
- Embedded mode
- Single-node server
- Vector search
- Full-text search
- Metadata filtering
- Consistent API across modes
- Multi-language clients
- Embedding function integrations
Only in Zilliz
- Vector indexing
- SQL interface
- Tensor support
- Real-time search
- Cloud-native
- Open-source compatible
Both cover
- Distributed architecture
What people use each for
The jobs each tool is most often brought in to do.
Chroma
- Prototyping retrieval-augmented generation where the priority is having a working index in minutes rather than choosing a permanent storenot Zilliz
- Agent memory in a single application process, where an embedded store avoids adding a network dependencynot Zilliz
- A departmental search application under roughly ten million records where one server is sufficient and simplicity is worth more than headroomnot Zilliz
- Local and CI testing of retrieval code with the same client library used in productionnot Zilliz
Zilliz
- Build retrieval-augmented generation (RAG) systemsnot Chroma
- Implement semantic search over documentsnot Chroma
- Create multimodal search with text and imagesnot Chroma
- Power recommendation engines with vector similaritynot Chroma
- Enable similarity search on user embeddingsnot Chroma
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Chroma
- On a single node, available memory sets a hard upper bound on collection size, roughly 245,000 records per gigabyte of RAM at 1024 dimensions, so capacity planning is a memory purchase and the ceiling arrives without warning.
- Single-node queries parallelise only up to the number of vCPUs, after which requests queue and latency rises linearly with concurrency, so throughput problems appear as a slow application rather than as errors.
- The distributed deployment behind Chroma Cloud is a different architecture from the embedded library, so latency, consistency and failure behaviour observed in a local prototype do not predict production behaviour.
- The open source server has no built-in authentication or multi-tenancy worth relying on, so a self-hosted deployment needs its own auth proxy and network controls before anything untrusted can reach it.
- The project has moved quickly through major internal rewrites and version changes, so upgrades have historically involved data migrations and client changes, and pinning versions is necessary rather than cautious.
Zilliz
- Pricing structure not publicly disclosed, requires sales contact
- Operational complexity for self-hosted Milvus deployments
- Learning curve for those unfamiliar with vector databases
- Limited built-in analytics compared to some alternatives
Pricing, plan by plan
Chroma
Free- StarterFree
- 10 databases
- 10 team members
- Community Slack access
- Team$250/month
- 100 databases
- 30 team members
- $100 in included credits
- Enterprise$null/month
- Unlimited databases
- Unlimited team members
- Dedicated support
Zilliz
FreeNo published plan breakdown. See the Zilliz review.
Which should you pick?
Choose Chroma if
- You need embedded mode.
- You want to start without paying.
- You also want single-node server.
Choose Zilliz if
- You need vector indexing.
- You want to start without paying.
- You work on Cloud, Self-hosted.
- You also want sql interface.
Questions people ask
- Is Chroma or Zilliz better?
- Neither clearly leads. Chroma starts at Free and Zilliz at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Chroma or Zilliz?
- Chroma starts at Free and Zilliz at Free.
- Does Chroma or Zilliz run on more platforms?
- Chroma runs on Web. Zilliz runs on Cloud, Self-hosted.
- Can I use Chroma for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Chroma best used for?
- Chroma is most often used for prototyping retrieval-augmented generation where the priority is having a working index in minutes rather than choosing a permanent store, agent memory in a single application process, where an embedded store avoids adding a network dependency, a departmental search application under roughly ten million records where one server is sufficient and simplicity is worth more than headroom, local and ci testing of retrieval code with the same client library used in production. Of those, prototyping retrieval-augmented generation where the priority is having a working index in minutes rather than choosing a permanent store and agent memory in a single application process, where an embedded store avoids adding a network dependency are not what Zilliz is typically brought in for.
- What can Chroma do that Zilliz cannot?
- Chroma covers Embedded mode, Single-node server, Vector search, Full-text search. Zilliz covers Vector indexing, SQL interface, Tensor support, Real-time search. Both handle Distributed architecture.
Answered from the vendors’ own pages
Chroma: Do I need to run a server?
No. Chroma runs embedded in your process with persistence to a local directory, which is how most projects start. The server and distributed modes exist for when multiple clients or larger collections require them.
Zilliz: What is the difference between Milvus and Zilliz Cloud?
Milvus is the open-source vector database that you can self-host. Zilliz Cloud is the fully managed service built on Milvus that removes operational overhead and handles scaling automatically.
SourceChroma: How large can a single node get?
The project puts single-node deployments at fewer than about ten million records across a handful of collections, with collection size bounded by system memory at roughly 245,000 records per gigabyte at 1024 dimensions.
Zilliz: How many vectors can Zilliz handle?
Milvus and Zilliz Cloud can store and search billions of vectors through their distributed architecture that separates storage and compute layers.
SourceChroma: Is Chroma Cloud the same software?
It is the same API and project, but the distributed deployment is a different architecture, using independent services, object storage and SSD caches rather than a single process. Behaviour under load differs accordingly.
Zilliz: Is Milvus open-source?
Yes, Milvus is open-source under the Apache License 2.0 and is part of the LF AI & Data Foundation.
SourceChroma: How does it compare with pgvector?
pgvector keeps vectors in a Postgres database you already operate, with SQL, joins and transactions. Chroma is a dedicated retrieval engine with a lower setup cost and a retrieval-shaped API. If you already run Postgres, pgvector removes a system; if you do not, Chroma removes a decision.
Zilliz: What pricing does Zilliz Cloud offer?
Zilliz Cloud pricing is not publicly listed and requires contacting their team to discuss your specific scale and use case requirements.
SourceChroma: What licence is it under?
Apache 2.0, which permits self-hosting and embedding in commercial products without a competing-use restriction.
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