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Databases · head to head

FaunaDB vs Google Vertex AI

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
Google Vertex AI logo

Google Vertex AI

Machine Learning

Unified ML platform to build, deploy, and scale AI models

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only FaunaDB has a free tier, so it costs nothing to try first.
  • Each has a real cost: 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.; Google Vertex AI vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult
  • They diverge on capability: FaunaDB covers Document-relational model, Google Vertex AI covers AutoML.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which FaunaDB and Google Vertex AI actually diverge.

Attributes where FaunaDB and Google Vertex AI differ
AttributeFaunaDBGoogle Vertex AI
Starting priceFreeOn request
Pricing modelfreemiumUnknown
Free tierYesNo
PlatformsWebCloud, Web
CategoryDatabasesMachine Learning
Founded20122008

Identical on both: user rating (Not yet rated).

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 FaunaDB

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

Only in Google Vertex AI

  • AutoML
  • Custom training
  • Feature Store
  • Model monitoring
  • Prediction serving
  • BigQuery
  • Cloud Storage
  • TensorFlow

What people use each for

The jobs each tool is most often brought in to do.

FaunaDB

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

Google Vertex AI

  • Machine learningnot FaunaDB
  • Data analysisnot FaunaDB
  • Model trainingnot FaunaDB
  • Predictive analyticsnot FaunaDB

Where each one falls short

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

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.

Google Vertex AI

  • Vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult
  • Requires familiarity with Google Cloud Platform infrastructure and concepts
  • Cost can escalate quickly with large training and inference workloads

Pricing, plan by plan

FaunaDB

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

Google Vertex AI

On request

No published plan breakdown. See the Google Vertex AI review.

Which should you pick?

Choose FaunaDB if

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

Choose Google Vertex AI if

  • You need automl.
  • You work on Cloud, Web.
  • You also want custom training.
Google Vertex AI review

Questions people ask

Is FaunaDB or Google Vertex AI better?
Neither clearly leads. FaunaDB starts at Free and Google Vertex AI at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, FaunaDB or Google Vertex AI?
FaunaDB has a free tier; the other does not. Paid plans start at Free for FaunaDB and On request for Google Vertex AI.
Does FaunaDB or Google Vertex AI run on more platforms?
FaunaDB runs on Web. Google Vertex AI runs on Cloud, Web.
Can I use FaunaDB for free?
Yes. FaunaDB has a free tier, so you can try it without paying. Google Vertex AI starts at On request.
What is FaunaDB best used for?
FaunaDB is most often used for keeping an existing fauna-backed application alive on self-hosted infrastructure while a migration is planned and funded, extracting historical data from a fauna dataset that can no longer be reached through the hosted api, studying a production implementation of deterministic distributed transactions, since the full server source is now readable under apache 2.0, forking the engine deliberately, where an organisation has jvm and distributed-systems staff and wants a document-relational store it fully controls. Of those, keeping an existing fauna-backed application alive on self-hosted infrastructure while a migration is planned and funded and extracting historical data from a fauna dataset that can no longer be reached through the hosted api are not what Google Vertex AI is typically brought in for.
What can FaunaDB do that Google Vertex AI cannot?
FaunaDB covers Document-relational model, FQL v10, Distributed ACID transactions, HTTPS access. Google Vertex AI covers AutoML, Custom training, Feature Store, Model monitoring.

Answered from the vendors’ own pages

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.

Google Vertex AI: What is the pricing model for Google Vertex AI?

Vertex AI uses a pay-as-you-go model with no upfront costs or lock-in fees. Costs vary by service: training is billed by compute resources and time (30-second increments), online predictions by machine type per hour, and batch predictions by compute time or per-record for specific AutoML types.

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.

Google Vertex AI: What types of data can Vertex AI handle?

Vertex AI supports image, video, text, and tabular data types with tools for uploading, storing, and managing large datasets.

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.

Google Vertex AI: Does Vertex AI support custom model training?

Yes. Vertex AI supports both AutoML for automated machine learning and custom training code in Python, R, and other languages.

Source
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.

Google Vertex AI: What deployment options are available in Vertex AI?

Vertex AI supports online predictions for real-time use cases and batch predictions for large-scale processing.

Source
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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