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Databases · head to head

Dremio vs YugabyteDB

Dremio logo

Dremio

Databases

SQL query engine and lakehouse layer over Iceberg tables in object storage

From
Free
Rated
-
Full reviewWebsite
YugabyteDB logo

YugabyteDB

Databases

Open source distributed SQL database for cloud native apps

From
Free
Rated
-
Full reviewWebsite

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.; YugabyteDB missing PostgreSQL functions and extensions despite claiming compatibility
  • They diverge on capability: Dremio covers Arrow-based execution, YugabyteDB covers PostgreSQL Compatible.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Dremio and YugabyteDB actually diverge.

Attributes where Dremio and YugabyteDB differ
AttributeDremioYugabyteDB
Pricing modelPer Dremio Compute Unit consumedUnknown
PlatformsLinux, Kubernetes, Cloud, DockerCloud, On-premises, Kubernetes
FoundedUnknown2016

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 YugabyteDB

  • PostgreSQL Compatible
  • Distributed SQL
  • Geo-distribution
  • Linear Scalability
  • High Availability
  • ACID Transactions
  • CDC Support
  • PostgreSQL

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 YugabyteDB
  • A data platform team standardising on Apache Iceberg and needing a SQL engine plus catalogue that does not lock the tables innot YugabyteDB
  • An analytics group accelerating slow lake queries with Reflections instead of hand-built aggregate tablesnot YugabyteDB
  • A regulated enterprise that must keep data on premises but wants a modern lakehouse SQL layernot YugabyteDB

YugabyteDB

  • Transaction processingnot Dremio
  • Data storagenot Dremio
  • Application backendnot Dremio
  • Reportingnot Dremio
  • Data analyticsnot 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.

YugabyteDB

  • Missing PostgreSQL functions and extensions despite claiming compatibility
  • Not a true PostgreSQL replacement requiring schema and query compatibility testing before migration
  • Requires careful isolation level management or risk data corruption in production
  • Lacks built-in OLAP capabilities, requiring external systems for analytics
  • Coupled compute and storage scaling reduces optimization flexibility

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

YugabyteDB

Free

No published plan breakdown. See the YugabyteDB review.

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.
Dremio review

Choose YugabyteDB if

  • You need postgresql compatible.
  • You want to start without paying.
  • You work on Cloud, On-premises, Kubernetes.
  • You also want distributed sql.
YugabyteDB review

Questions people ask

Is Dremio or YugabyteDB better?
Neither clearly leads. Dremio starts at Free and YugabyteDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dremio or YugabyteDB?
Dremio starts at Free and YugabyteDB at Free.
Does Dremio or YugabyteDB run on more platforms?
Dremio runs on Linux, Kubernetes, Cloud, Docker. YugabyteDB runs on Cloud, On-premises, Kubernetes.
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 YugabyteDB is typically brought in for.
What can Dremio do that YugabyteDB cannot?
Dremio covers Arrow-based execution, Reflections, Semantic layer, Iceberg catalogue. YugabyteDB covers PostgreSQL Compatible, Distributed SQL, Geo-distribution, Linear Scalability.

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.

YugabyteDB: Is YugabyteDB a true drop-in replacement for PostgreSQL?

No, YugabyteDB is PostgreSQL-compatible but not a zero-change drop-in replacement. It requires compatibility testing with queries, stored procedures, and ORM configurations before migration.

Source
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.

YugabyteDB: What isolation levels does YugabyteDB support?

YugabyteDB allows per-query selection between serializable isolation for critical operations and read-committed for analytics. However, this flexibility requires careful management to avoid accidental data corruption.

Source
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.

YugabyteDB: Does YugabyteDB support both SQL and NoSQL workloads?

Yes, YugabyteDB offers YSQL for PostgreSQL-compatible SQL and YCQL for Cassandra-like NoSQL workloads, using the same DocDB storage engine to support both simultaneously.

Source
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.

YugabyteDB: Can YugabyteDB scale compute and storage independently?

No, YugabyteDB couples compute and storage scaling, unlike TiDB which separates them. This means scaling decisions are less flexible and optimization is more complex.

Source
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