Databases · head to head
Dremio vs FaunaDB

Dremio
Databases
SQL query engine and lakehouse layer over Iceberg tables in object storage
- From
- Free
- Rated
- -

FaunaDB
Databases
Document-relational database whose hosted service closed in 2025 and whose core is now unmaintained Apache 2.0 code.
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Dremio reflections consume compute and storage to build and refresh continuously, so a team that enables them widely discovers that background maintenance rather than user queries drives the DCU bill.; 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: Dremio covers Arrow-based execution, FaunaDB covers Document-relational model.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which Dremio and FaunaDB actually diverge.
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 Dremio
- Arrow-based execution
- Reflections
- Semantic layer
- Iceberg catalogue
- Federated queries
- Autonomous management
- Fine-grained access control
- BI connectors
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.
Dremio
- A company with petabytes of Parquet in S3 that wants BI dashboards without duplicating it into a warehousenot FaunaDB
- A data platform team standardising on Apache Iceberg and needing a SQL engine plus catalogue that does not lock the tables innot FaunaDB
- An analytics group accelerating slow lake queries with Reflections instead of hand-built aggregate tablesnot FaunaDB
- A regulated enterprise that must keep data on premises but wants a modern lakehouse SQL layernot FaunaDB
FaunaDB
- Keeping an existing Fauna-backed application alive on self-hosted infrastructure while a migration is planned and fundednot Dremio
- Extracting historical data from a Fauna dataset that can no longer be reached through the hosted APInot Dremio
- Studying a production implementation of deterministic distributed transactions, since the full server source is now readable under Apache 2.0not Dremio
- Forking the engine deliberately, where an organisation has JVM and distributed-systems staff and wants a document-relational store it fully controlsnot Dremio
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Dremio
- Reflections consume compute and storage to build and refresh continuously, so a team that enables them widely discovers that background maintenance rather than user queries drives the DCU bill.
- Self-managing Dremio on Kubernetes requires real platform engineering capacity for tuning executors, memory and coordinator sizing, and it is not comparable in effort to running a managed warehouse.
- The Community Edition lacks the security and governance features most enterprises require, so the free tier is a trial path rather than a viable production option for regulated buyers.
- Dremio Cloud is AWS-first, which leaves Azure and Google Cloud customers on the self-managed path with the operational burden that entails.
- Query performance without Reflections on raw, poorly laid out files is often unremarkable, so the promise of querying the lake as is depends on file layout work you still have to do.
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
Dremio
Free- Community EditionFree
- Self-managed on your own hardware
- SQL engine and semantic layer
- No vendor support
- Dremio Cloud$0.2/hour
- Billed at $0.20 per Dremio Compute Unit
- Includes query execution, Reflections and background processing
- 400 dollar trial credit for 30 days
- Enterprise$undefined/year
- Self-managed on Kubernetes, on premises or any cloud
- Enterprise security, SSO and governance
- Vendor support with SLA
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 Dremio if
- You need arrow-based execution.
- You want to start without paying.
- You work on Linux, Kubernetes, Cloud, Docker.
- You also want reflections.
Choose FaunaDB if
- You need document-relational model.
- You want to start without paying.
- You also want fql v10.
Questions people ask
- Is Dremio or FaunaDB better?
- Neither clearly leads. Dremio 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, Dremio or FaunaDB?
- Dremio starts at Free and FaunaDB at Free.
- Does Dremio or FaunaDB run on more platforms?
- Dremio runs on Linux, Kubernetes, Cloud, Docker. FaunaDB runs on Web.
- Can I use Dremio for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Dremio best used for?
- Dremio is most often used for a company with petabytes of parquet in s3 that wants bi dashboards without duplicating it into a warehouse, a data platform team standardising on apache iceberg and needing a sql engine plus catalogue that does not lock the tables in, an analytics group accelerating slow lake queries with reflections instead of hand-built aggregate tables, a regulated enterprise that must keep data on premises but wants a modern lakehouse sql layer. Of those, a company with petabytes of parquet in s3 that wants bi dashboards without duplicating it into a warehouse and a data platform team standardising on apache iceberg and needing a sql engine plus catalogue that does not lock the tables in are not what FaunaDB is typically brought in for.
- What can Dremio do that FaunaDB cannot?
- Dremio covers Arrow-based execution, Reflections, Semantic layer, Iceberg catalogue. FaunaDB covers Document-relational model, FQL v10, Distributed ACID transactions, HTTPS access.
Answered from the vendors’ own pages
Dremio: How is Dremio Cloud billed?
At 0.20 US dollars per Dremio Compute Unit, which counts query execution, Reflection building and platform overhead, not just user queries.
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.
Dremio: Is there a free version?
Yes, a Community Edition you self-manage, but it omits the enterprise security and governance features and comes with no support.
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.
Dremio: Does it lock in my data?
No, tables stay in Apache Iceberg or Parquet in your own object storage and can be read by Spark, Trino or other engines.
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.
Dremio: Do I still need a warehouse?
Often not for analytics, but Dremio is not a transactional store and high-concurrency operational serving is not its strength.
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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