Databases · head to head
Chroma vs Cortex
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
- Free plan
- Yes
Cortex
Developer Tools
Internal developer portal that scores service ownership and maturity rather than just cataloguing services
- From
- On request
- Free plan
- No
The short version
- Chroma starts at $250/mo; Cortex prices on request.
- Only Chroma lists embedded mode; only Cortex lists service catalogue.
- Prices and features on this page were last checked on 13 November 2026.
Where they differ
Only the attributes on which Chroma and Cortex actually diverge.
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 Cortex
- Service catalogue
- Scorecards
- Initiatives
- Self-service templates
- Query language
- Eng intelligence
- Integrations layer
- On-call and ownership mapping
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 Cortex
- Agent memory in a single application process, where an embedded store avoids adding a network dependencynot Cortex
- A departmental search application under roughly ten million records where one server is sufficient and simplicity is worth more than headroomnot Cortex
- Local and CI testing of retrieval code with the same client library used in productionnot Cortex
Cortex
- A platform team that needs to prove to leadership how far a Kubernetes or framework migration has actually progressed across hundreds of servicesnot Chroma
- An organisation where ownership of production services is genuinely unknown after reorganisations or acquisitionsnot Chroma
- Enforcing production readiness standards on new services at creation time rather than at incident reviewnot Chroma
- Replacing a self-hosted Backstage that is consuming a full-time engineer or two just to stay upgradednot 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
Cortex
- Pricing is quote only, so a platform team cannot build a business case or compare against the true cost of self-hosted Backstage without entering a sales cycle first
- The catalogue is only as accurate as the metadata you supply, so an organisation with inconsistent repository conventions spends its first quarter cleaning data before any scorecard means anything
- Scorecards create political friction: publishing a per-team grade turns an engineering standard into a performance metric, and teams will game the rules rather than fix the underlying issue
- It is closed source and hosted, so organisations with strict data residency or air-gap requirements have limited options compared with running Backstage themselves
- Value scales with organisation size, so a company with fifty engineers and thirty services will find the catalogue tells them nothing they did not already know while still paying an enterprise contract
Pricing, plan by plan
Chroma
Free- StarterFree
- 10 databases
- 10 team members
- Community Slack access
- Team$250/mo
- 100 databases
- 30 team members
- $100 in included credits
- EnterpriseOn request
- Unlimited databases
- Unlimited team members
- Dedicated support
Cortex
On request- CortexOn request
- Service catalogue and ownership mapping
- Scorecards and initiatives
- Self-service templates
Which should you pick?
Choose Chroma if
- You need embedded mode.
- You want to start without paying.
- You also want single-node server.
Choose Cortex if
- You need service catalogue.
- You work on Web, API.
- You also want scorecards.
Questions people ask
- Is Chroma or Cortex better?
- Neither clearly leads. Chroma starts at Free and Cortex at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Chroma or Cortex?
- Chroma has a free tier; the other does not. Paid plans start at Free for Chroma and On request for Cortex.
- Does Chroma or Cortex run on more platforms?
- Chroma runs on Web. Cortex runs on Web, API.
- Can I use Chroma for free?
- Yes. Chroma has a free tier, so you can try it without paying. Cortex 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 Cortex is typically brought in for.
- What can Chroma do that Cortex cannot?
- Chroma covers Embedded mode, Single-node server, Distributed architecture, Vector search. Cortex covers Service catalogue, Scorecards, Initiatives, Self-service templates.
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.
Cortex: How is Cortex different from Backstage?
Backstage is an open source framework you build and staff. Cortex is a hosted product with scorecards and initiatives out of the box and no platform team required to keep it running.
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.
Cortex: Is pricing published?
No. Cortex requires a sales conversation and prepares a custom proposal.
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.
Cortex: Can it self-host?
It is offered as a hosted product; on-premise arrangements are handled through sales rather than published.
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.
Cortex: What is the main adoption risk?
Bad or missing service metadata. The catalogue and every scorecard on top of it inherit whatever quality your repositories already have.
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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- Cortex vs Tilt
- Cortex vs Vim
- Cortex vs WarpBuild
- Cortex vs Webpack
- Cortex vs Avo
- Cortex vs Azure DevOps