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Machine Learning · head to head

AWS SageMaker vs FaunaDB

AWS SageMaker logo

AWS SageMaker

Machine Learning

Build, train, and deploy machine learning models at scale

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: AWS SageMaker vendor lock-in to AWS ecosystem makes migration to other platforms difficult; 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: AWS SageMaker covers Jupyter notebooks, FaunaDB covers Document-relational model.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which AWS SageMaker and FaunaDB actually diverge.

Attributes where AWS SageMaker and FaunaDB differ
AttributeAWS SageMakerFaunaDB
Pricing modelUnknownfreemium
CategoryMachine LearningDatabases
Founded20062012

Identical on both: starting price (Free), free tier (Yes), platforms (Web), 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 AWS SageMaker

  • Jupyter notebooks
  • Built-in algorithms
  • Automatic model tuning
  • One-click deployment
  • Model monitoring
  • S3
  • Lambda
  • Step Functions

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.

AWS SageMaker

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

FaunaDB

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

Where each one falls short

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

AWS SageMaker

  • Vendor lock-in to AWS ecosystem makes migration to other platforms difficult
  • Opaque pricing can lead to unexpected expenses like forgotten EBS volume charges
  • Does not include native job scheduling, requiring Lambda or EventBridge integration

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

AWS SageMaker

Free

No published plan breakdown. See the AWS SageMaker 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 AWS SageMaker if

  • You need jupyter notebooks.
  • You want to start without paying.
  • You also want built-in algorithms.
AWS SageMaker 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 AWS SageMaker or FaunaDB better?
Neither clearly leads. AWS SageMaker 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, AWS SageMaker or FaunaDB?
AWS SageMaker starts at Free and FaunaDB at Free.
Does AWS SageMaker or FaunaDB run on more platforms?
Both run on Web, so platform support will not decide this one for you.
Can I use AWS SageMaker for free?
Both have a free tier, so you can try either at no cost before committing.
What is AWS SageMaker best used for?
AWS SageMaker is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what FaunaDB is typically brought in for.
What can AWS SageMaker do that FaunaDB cannot?
AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. FaunaDB covers Document-relational model, FQL v10, Distributed ACID transactions, HTTPS access.

Answered from the vendors’ own pages

AWS SageMaker: What is AWS SageMaker used for?

AWS SageMaker is a machine learning service for building, training, and deploying ML models at scale. It provides tools for data preparation, model training, inference endpoints, and performance optimization.

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.

AWS SageMaker: How is AWS SageMaker priced?

SageMaker uses pay-as-you-go pricing with no upfront costs or long-term commitments. Pricing starts at $0.04 per hour for basic notebook instances and scales based on instance type. ML Savings Plans offer up to 64% off with hourly spend commitments.

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.

AWS SageMaker: Does AWS SageMaker have a free tier?

Yes, the free tier includes 250 hours of notebook usage, 50 hours of training, and 125 hours of hosting on ml.t3.medium instances during the first two months.

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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