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Databases · head to head

ClickHouse vs FaunaDB

ClickHouse logo

ClickHouse

Databases

Fast open-source column-oriented database for real-time analytics

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: ClickHouse limited multi-row atomic transactions and expensive UPDATE/DELETE operations unsuitable for transactional systems; 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: ClickHouse covers Column-oriented Storage, FaunaDB covers Document-relational model.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which ClickHouse and FaunaDB actually diverge.

Attributes where ClickHouse and FaunaDB differ
AttributeClickHouseFaunaDB
Pricing modelUnknownfreemium
PlatformsLinux, macOS, Windows (via Docker)Web
Founded20212012

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 ClickHouse

  • Column-oriented Storage
  • Real-time Analytics
  • SQL Support
  • Linear Scalability
  • Data Compression
  • Vectorized Query Execution
  • Approximate Calculations
  • Kafka

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.

ClickHouse

  • Business intelligencenot FaunaDB
  • Data warehousingnot FaunaDB
  • Real-time analyticsnot FaunaDB
  • Reportingnot FaunaDB
  • Machine learningnot FaunaDB

FaunaDB

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

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

ClickHouse

  • Limited multi-row atomic transactions and expensive UPDATE/DELETE operations unsuitable for transactional systems
  • Requires upfront schema design discipline with MergeTree engine choices and sort/partition keys
  • Experimental vector search support, not production-ready for vector operations
  • Different query syntax from standard SQL requiring migration planning
  • Limited JOIN capabilities compared to traditional relational databases
  • Migration complexity with 2-4 weeks estimated for data type mapping and query translation

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

ClickHouse

Free

No published plan breakdown. See the ClickHouse review.

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 ClickHouse if

  • You need column-oriented storage.
  • You want to start without paying.
  • You work on Linux, macOS, Windows (via Docker).
  • You also want real-time analytics.
ClickHouse 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 ClickHouse or FaunaDB better?
Neither clearly leads. ClickHouse 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, ClickHouse or FaunaDB?
ClickHouse starts at Free and FaunaDB at Free.
Does ClickHouse or FaunaDB run on more platforms?
ClickHouse runs on Linux, macOS, Windows (via Docker). FaunaDB runs on Web.
Can I use ClickHouse for free?
Both have a free tier, so you can try either at no cost before committing.
What is ClickHouse best used for?
ClickHouse is most often used for business intelligence, data warehousing, real-time analytics, reporting. Of those, business intelligence and data warehousing are not what FaunaDB is typically brought in for.
What can ClickHouse do that FaunaDB cannot?
ClickHouse covers Column-oriented Storage, Real-time Analytics, SQL Support, Linear Scalability. FaunaDB covers Document-relational model, FQL v10, Distributed ACID transactions, HTTPS access.

Answered from the vendors’ own pages

ClickHouse: What is ClickHouse best used for?

ClickHouse is optimized for analytical workloads on large datasets. It excels at fast aggregations and queries, being 10-100x faster than PostgreSQL on large aggregations.

Source
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.

ClickHouse: Does ClickHouse support transactions?

ClickHouse has limited transaction support and expensive UPDATE/DELETE operations. It is not suitable for transactional workloads requiring strict ACID guarantees.

Source
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.

ClickHouse: How does ClickHouse compare to PostgreSQL?

ClickHouse is 10-100x faster for analytics but PostgreSQL is better for transactional workloads. Many teams use both: PostgreSQL for writes via MaterializedPostgreSQL replication to ClickHouse for analytics.

Source
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.

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.

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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