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Databases · head to head

Chroma vs Immuta

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
Immuta logo

Immuta

Databases

Attribute-based access control and masking applied inside Snowflake, Databricks and BigQuery

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only Chroma has a free tier, so it costs nothing to try first.
  • 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.; Immuta contracts commonly start around one hundred to two hundred thousand US dollars a year for mid-market deployments and exceed five hundred thousand at enterprise scale, which excludes most data teams without a regulatory mandate.
  • They diverge on capability: Chroma covers Embedded mode, Immuta covers Attribute-based policy.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Chroma and Immuta actually diverge.

Attributes where Chroma and Immuta differ
AttributeChromaImmuta
Starting priceFreeOn request
Pricing modelusage-basedquote
Free tierYesNo
PlatformsWebWeb, API, Cloud

Identical on both: 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 Immuta

  • Attribute-based policy
  • Native enforcement
  • Dynamic masking
  • Row-level filtering
  • Purpose-based access
  • Sensitive data tagging
  • Audit logging
  • Multi-platform

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

Immuta

  • A bank whose Snowflake estate has grown to tens of thousands of roles that no one can review before an auditnot Chroma
  • A healthcare analytics team that must let researchers query patient data with identifiers masked unless a specific purpose is recordednot Chroma
  • A multinational applying different residency and access rules per jurisdiction to the same tables without duplicating datasetsnot Chroma
  • An organisation running both Snowflake and Databricks that wants one policy set rather than two divergent implementationsnot 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.

Immuta

  • Contracts commonly start around one hundred to two hundred thousand US dollars a year for mid-market deployments and exceed five hundred thousand at enterprise scale, which excludes most data teams without a regulatory mandate.
  • Policy is only as good as the data classification underneath it, so an organisation with poorly tagged columns will spend months on classification before Immuta enforces anything useful.
  • Native enforcement means capability varies by platform, and a feature available on Snowflake may be absent or behave differently on BigQuery, which undermines the promise of one policy set everywhere.
  • Adding an access governance layer creates a new dependency in the path to data: a misconfigured policy silently returns fewer rows rather than erroring, and analysts can act on incomplete results without noticing.
  • It governs cloud data platforms, so personal data in operational databases, files and SaaS applications sits outside its scope and needs separate controls, meaning Immuta is rarely the whole answer.

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

Immuta

On request
  • Immuta Platform$undefined/year
    • Attribute-based policy authoring
    • Native enforcement in supported data platforms
    • Dynamic masking and row-level security

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 Immuta if

  • You need attribute-based policy.
  • You work on Web, API, Cloud.
  • You also want native enforcement.
Immuta review

Questions people ask

Is Chroma or Immuta better?
Neither clearly leads. Chroma starts at Free and Immuta at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Chroma or Immuta?
Chroma has a free tier; the other does not. Paid plans start at Free for Chroma and On request for Immuta.
Does Chroma or Immuta run on more platforms?
Chroma runs on Web. Immuta runs on Web, API, Cloud.
Can I use Chroma for free?
Yes. Chroma has a free tier, so you can try it without paying. Immuta starts at On request.
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 Immuta is typically brought in for.
What can Chroma do that Immuta cannot?
Chroma covers Embedded mode, Single-node server, Distributed architecture, Vector search. Immuta covers Attribute-based policy, Native enforcement, Dynamic masking, Row-level filtering.

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.

Immuta: Does Immuta sit in the query path?

No. It compiles policies into the data platform's own native controls, so queries run at normal speed through your existing tools.

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.

Immuta: What does it cost?

Not published. Market data suggests roughly 100,000 to 200,000 US dollars a year for mid-market deployments and considerably more at enterprise scale.

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.

Immuta: Is Immuta still independent?

Yes. It remains independently owned, unlike several competitors in data access governance that have been acquired.

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.

Immuta: Does it work across more than one warehouse?

Yes, one policy set can target Snowflake, Databricks, BigQuery and Starburst, though enforcement capability varies by platform.

Chroma: 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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