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Databases · head to head

Chroma vs QuestDB

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
QuestDB logo

QuestDB

Databases

Fast open source time-series database for high throughput ingestion

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.; QuestDB open-source edition lacks high-availability, distributed architecture, and enterprise security features
  • They diverge on capability: Chroma covers Embedded mode, QuestDB covers High Throughput Ingestion.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Chroma and QuestDB actually diverge.

Attributes where Chroma and QuestDB differ
AttributeChromaQuestDB
Pricing modelusage-basedopen-source
PlatformsWebDocker, Kubernetes, Cloud (AWS, Azure, GCP)
FoundedUnknown2014

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
  • Distributed architecture
  • Vector search
  • Full-text search
  • Metadata filtering
  • Consistent API across modes
  • Multi-language clients

Only in QuestDB

  • High Throughput Ingestion
  • SQL Support
  • Time-series Optimization
  • SIMD Vectorization
  • Column-oriented Storage
  • Built-in Web Console
  • InfluxDB Line Protocol
  • PostgreSQL

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

QuestDB

  • Time-series analytics ingesting up to 20M rows/second from IoT sensors or financial data feedsnot Chroma
  • Real-time dashboarding with 32ms time-to-first-row latency for minute-level analyticsnot Chroma
  • Applications requiring multi-tier storage (hot ingest, real-time SQL, cold Parquet archive)not 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.

QuestDB

  • Open-source edition lacks high-availability, distributed architecture, and enterprise security features
  • Enterprise edition pricing not published; requires contacting sales for custom quote
  • Ingestion limit of 20M rows/sec platform-dependent; may not scale to extreme throughput requirements

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

QuestDB

Free

No published plan breakdown. See the QuestDB review.

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 QuestDB if

  • You need high throughput ingestion.
  • You want to start without paying.
  • You work on Docker, Kubernetes, Cloud (AWS, Azure, GCP).
  • You also want sql support.
QuestDB review

Questions people ask

Is Chroma or QuestDB better?
Neither clearly leads. Chroma starts at Free and QuestDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Chroma or QuestDB?
Chroma starts at Free and QuestDB at Free.
Does Chroma or QuestDB run on more platforms?
Chroma runs on Web. QuestDB runs on Docker, Kubernetes, Cloud (AWS, Azure, GCP).
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 QuestDB is typically brought in for.
What can Chroma do that QuestDB cannot?
Chroma covers Embedded mode, Single-node server, Distributed architecture, Vector search. QuestDB covers High Throughput Ingestion, SQL Support, Time-series Optimization, SIMD Vectorization.

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.

QuestDB: How much does QuestDB Enterprise cost?

QuestDB does not publish specific pricing for the Enterprise tier. Customers must contact QuestDB via their enterprise contact form to receive a custom quote.

Source
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.

QuestDB: Does QuestDB offer a free version?

Yes, QuestDB Open Source is completely free and recommended for evaluation, prototyping, and pilot projects. Enterprise features, high availability, security, and dedicated support require the paid Enterprise tier.

Source
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.

QuestDB: What deployment options does QuestDB offer?

QuestDB offers open source deployment, Enterprise deployment, and Bring Your Own Cloud (BYOC) deployment. Pricing details for BYOC and Enterprise tiers are not published and require direct contact with sales.

Source
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.

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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