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Databases · head to head

Chroma vs FaunaDB

Chroma logo

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
-
Full reviewWebsite
FaunaDB logo

FaunaDB

Databases

Document-relational database whose hosted service closed in 2025 and whose core is now unmaintained Apache 2.0 code.

From
Free
Rated
-
Full reviewWebsite

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.; FaunaDB the hosted service was wound down in 2025, so there is no managed Fauna to buy; every remaining user either operates a JVM cluster themselves or migrates, and both are projects rather than tasks.
  • They diverge on capability: Chroma covers Embedded mode, FaunaDB covers Document-relational model.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Chroma and FaunaDB actually diverge.

Attributes where Chroma and FaunaDB differ
AttributeChromaFaunaDB
Pricing modelusage-basedfreemium
FoundedUnknown2012

Identical on both: starting price (Free), free tier (Yes), platforms (Web), 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
  • Distributed architecture
  • Vector search
  • Full-text search
  • Metadata filtering
  • Consistent API across modes
  • Multi-language clients

Only in FaunaDB

  • Document-relational model
  • FQL v10
  • Distributed ACID transactions
  • HTTPS access
  • User-defined functions
  • Attribute-based access control
  • Document history
  • Event streaming

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 FaunaDB
  • Agent memory in a single application process, where an embedded store avoids adding a network dependencynot FaunaDB
  • A departmental search application under roughly ten million records where one server is sufficient and simplicity is worth more than headroomnot FaunaDB
  • Local and CI testing of retrieval code with the same client library used in productionnot FaunaDB

FaunaDB

  • Keeping an existing Fauna-backed application alive on self-hosted infrastructure while a migration is planned and fundednot Chroma
  • Extracting historical data from a Fauna dataset that can no longer be reached through the hosted APInot Chroma
  • Studying a production implementation of deterministic distributed transactions, since the full server source is now readable under Apache 2.0not Chroma
  • Forking the engine deliberately, where an organisation has JVM and distributed-systems staff and wants a document-relational store it fully controlsnot 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.

FaunaDB

  • The hosted service was wound down in 2025, so there is no managed Fauna to buy; every remaining user either operates a JVM cluster themselves or migrates, and both are projects rather than tasks.
  • The open-sourced repository has had no substantive activity since May 2025 and the drivers were frozen alongside it, so you inherit responsibility for security patches in a Scala distributed database that almost nobody else is running.
  • FQL has no wire or dialect compatibility with anything else, so migrating off is a rewrite of every query, index and access rule in the application rather than a data export.
  • No BI tool, ORM or CDC connector speaks FQL, so reporting and analytics always required exporting the data first, and that export tooling is now also unmaintained.
  • The community was small before the shutdown and has dispersed since, so operational answers, tuning advice and people who have run a Fauna cluster in anger are all scarce when something breaks.

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

FaunaDB

Free
  • FreeFree
    • 100K read ops
    • 50K write ops
    • 1GB storage
  • Pro$25/month
    • Pay per use
    • Priority support
    • Advanced features

Which should you pick?

Choose Chroma if

  • You need embedded mode.
  • You want to start without paying.
  • You also want single-node server.
Chroma review

Choose FaunaDB if

  • You need document-relational model.
  • You want to start without paying.
  • You also want fql v10.
FaunaDB review

Questions people ask

Is Chroma or FaunaDB better?
Neither clearly leads. Chroma starts at Free and FaunaDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Chroma or FaunaDB?
Chroma starts at Free and FaunaDB at Free.
Does Chroma or FaunaDB run on more platforms?
Both run on Web, so platform support will not decide this one for you.
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 FaunaDB is typically brought in for.
What can Chroma do that FaunaDB cannot?
Chroma covers Embedded mode, Single-node server, Distributed architecture, Vector search. FaunaDB covers Document-relational model, FQL v10, Distributed ACID transactions, HTTPS access.

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.

FaunaDB: Can I still sign up for Fauna as a service?

No. Fauna Inc. wound down the hosted service in 2025 and the company website is no longer serving. The only way to run Fauna now is to build and operate the open-sourced server yourself.

Chroma: 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.

FaunaDB: What licence is the open-sourced code under?

Apache 2.0, with the copyright held by a FaunaDB Foundation. That is a permissive OSI licence with no competing-use clause, so you may run it, modify it and even offer it as a service.

Chroma: 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.

FaunaDB: Is the open source version the same software that ran the cloud?

It is the core database engine. The control plane, billing, dashboard and multi-tenant operational tooling that made it a service are not part of the release, so you are running the engine, not the product.

Chroma: 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.

FaunaDB: What should I migrate to?

There is no drop-in target. Teams that valued the document model with relationships usually land on Postgres with JSONB, and teams that valued the serverless HTTP access pattern usually land on DynamoDB or a managed Postgres with an HTTP driver. Either way the query layer is rewritten.

Chroma: What licence is it under?

Apache 2.0, which permits self-hosting and embedding in commercial products without a competing-use restriction.

FaunaDB: How hard is it to self-host?

It builds as a fat JAR and runs as a multi-node JVM cluster. There is an OPERATING.md, but no supported packaging, no operator, no upstream releases and no support contract, so budget for a distributed-systems engineer, not a container.

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