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Databases · head to head

Amazon Aurora vs Dremio

Amazon Aurora logo

Amazon Aurora

Databases

MySQL and PostgreSQL-compatible relational database built for the cloud

From
Free
Rated
-
Full reviewWebsite
Dremio logo

Dremio

Databases

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

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Amazon Aurora aurora requires AWS ecosystem knowledge and integration with other AWS services; 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.
  • They diverge on capability: Amazon Aurora covers MySQL/PostgreSQL Compatible, Dremio covers Arrow-based execution.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Amazon Aurora and Dremio actually diverge.

Attributes where Amazon Aurora and Dremio differ
AttributeAmazon AuroraDremio
Pricing modelusage-basedPer Dremio Compute Unit consumed
PlatformsAWS CloudLinux, Kubernetes, Cloud, Docker
Founded2006Unknown

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 Amazon Aurora

  • MySQL/PostgreSQL Compatible
  • 5x MySQL Performance
  • Auto-scaling Storage
  • Global Database
  • Serverless v2
  • Multi-master
  • Fault Tolerant
  • AWS Lambda

Only in Dremio

  • Arrow-based execution
  • Reflections
  • Semantic layer
  • Iceberg catalogue
  • Federated queries
  • Autonomous management
  • Fine-grained access control
  • BI connectors

What people use each for

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

Amazon Aurora

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

Dremio

  • A company with petabytes of Parquet in S3 that wants BI dashboards without duplicating it into a warehousenot Amazon Aurora
  • A data platform team standardising on Apache Iceberg and needing a SQL engine plus catalogue that does not lock the tables innot Amazon Aurora
  • An analytics group accelerating slow lake queries with Reflections instead of hand-built aggregate tablesnot Amazon Aurora
  • A regulated enterprise that must keep data on premises but wants a modern lakehouse SQL layernot Amazon Aurora

Where each one falls short

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

Amazon Aurora

  • Aurora requires AWS ecosystem knowledge and integration with other AWS services
  • Pricing can become expensive with high-traffic applications using many read replicas
  • Limited support for non-relational data types compared to NoSQL alternatives

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.

Pricing, plan by plan

Amazon Aurora

Free
  • Serverless v2$0.12/hour
    • Auto-scaling
    • Pay per ACU
    • Instant scaling
  • Provisioned$29/month
    • Dedicated instances
    • Predictable performance
    • Reserved capacity

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

Which should you pick?

Choose Amazon Aurora if

  • You need mysql/postgresql compatible.
  • You want to start without paying.
  • You work on AWS Cloud.
  • You also want 5x mysql performance.
Amazon Aurora review

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

Questions people ask

Is Amazon Aurora or Dremio better?
Neither clearly leads. Amazon Aurora starts at Free and Dremio at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Amazon Aurora or Dremio?
Amazon Aurora starts at Free and Dremio at Free.
Does Amazon Aurora or Dremio run on more platforms?
Amazon Aurora runs on AWS Cloud. Dremio runs on Linux, Kubernetes, Cloud, Docker.
Can I use Amazon Aurora for free?
Both have a free tier, so you can try either at no cost before committing.
What is Amazon Aurora best used for?
Amazon Aurora is most often used for transaction processing, data storage, application backend, reporting. Of those, transaction processing and data storage are not what Dremio is typically brought in for.
What can Amazon Aurora do that Dremio cannot?
Amazon Aurora covers MySQL/PostgreSQL Compatible, 5x MySQL Performance, Auto-scaling Storage, Global Database. Dremio covers Arrow-based execution, Reflections, Semantic layer, Iceberg catalogue.

Answered from the vendors’ own pages

Amazon Aurora: Is Amazon Aurora compatible with MySQL and PostgreSQL?

Yes, Amazon Aurora offers MySQL and PostgreSQL compatibility with full compatibility to their open-source counterparts, allowing you to migrate existing databases with standard tools.

Source
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.

Amazon Aurora: What uptime SLA does Amazon Aurora provide?

Aurora is designed for up to 99.99% single-region uptime and 99.999% multi-region uptime with automatic failover.

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.

Amazon Aurora: How much does Amazon Aurora cost?

Aurora uses serverless, usage-based pricing where you pay only for consumed capacity. Typical pricing ranges from $50-70 per month for minimal setups to $400-600 per month for small production clusters.

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.

Amazon Aurora: Can Amazon Aurora scale automatically?

Yes, Aurora automatically scales to match workload demands without performance degradation, supporting both read and write scaling.

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.

Amazon Aurora: How many read replicas does Aurora support?

Aurora supports up to 15 low-latency read replicas for distributing read traffic across your application.

Source
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