Softwr

Databases · head to head

Dremio vs Tinybird

Dremio logo

Dremio

Databases

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

From
Free
Rated
-
Full reviewWebsite
Tinybird logo

Tinybird

Databases

Managed ClickHouse with a workflow that turns SQL queries into hosted HTTP APIs

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.; Tinybird it is ClickHouse underneath, so it inherits ClickHouse limits: multi-table joins degrade badly at scale, updates and deletes are expensive mutations rather than cheap operations, and a poorly chosen sorting key at table creation cannot be fixed without rebuilding the data.
  • They diverge on capability: Dremio covers Arrow-based execution, Tinybird covers Managed ClickHouse.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Dremio and Tinybird actually diverge.

Attributes where Dremio and Tinybird differ
AttributeDremioTinybird
Pricing modelPer Dremio Compute Unit consumedPer month by compute and storage
PlatformsLinux, Kubernetes, Cloud, DockerWeb, Cloud, Linux, macOS

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 Tinybird

  • Managed ClickHouse
  • Pipes as APIs
  • Events HTTP endpoint
  • Streaming connectors
  • Materialized views
  • Git-based workflow
  • Token-scoped auth
  • Observability

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

Tinybird

  • A SaaS product adding a per-customer usage dashboard that must render in under a second across billions of eventsnot Dremio
  • A team building rate limiting or fraud checks that need an aggregate over the last few minutes returned inside a request cyclenot Dremio
  • A data team offloading interactive operational dashboards from Snowflake, where per-query warehouse cost makes constant refresh untenablenot Dremio
  • A game or ad-tech company ingesting a high-volume event stream and exposing live counters back to customers through an APInot 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.

Tinybird

  • It is ClickHouse underneath, so it inherits ClickHouse limits: multi-table joins degrade badly at scale, updates and deletes are expensive mutations rather than cheap operations, and a poorly chosen sorting key at table creation cannot be fixed without rebuilding the data.
  • Compute is metered per vCPU-second with overage at 0.0002 USD per second, so an inefficient query shipped to production shows up directly on the invoice rather than merely running slowly.
  • Only the Enterprise tier gets horizontal scaling and dedicated infrastructure; Free, Developer and SaaS all run on shared infrastructure with vertical scaling only, which caps both isolation and headroom for anyone not on a custom contract.
  • Storage is billed at 0.058 USD per gigabyte on top of compute, and egress is charged separately at 0.01 USD per gigabyte intra-cloud and 0.10 USD inter-cloud, so a high-fanout API serving many small responses accrues costs in three places at once.
  • You are building on a proprietary workflow around an open database: the pipes, tokens and API layer are Tinybird specific, so leaving means keeping your data but rewriting the entire serving layer you adopted Tinybird to avoid writing.

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

Tinybird

Free
  • FreeFree
    • 0.25 vCPU on shared infrastructure
    • 10 GB storage included
    • 1,000 requests per day
  • Developer$25/month
    • 0.5 vCPU scaling to 8 vCPU
    • 25 GB storage included
    • Two replicas
  • SaaS$undefined/month
    • Up to 32 vCPU
    • 500 GB storage included
    • Four to sixteen threads per request
  • Enterprise$undefined/year
    • Unlimited vCPU and bottomless storage
    • Dedicated infrastructure and private regions
    • Vertical and horizontal scaling

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 Tinybird if

  • You need managed clickhouse.
  • You want to start without paying.
  • You work on Web, Cloud, Linux, macOS.
  • You also want pipes as apis.
Tinybird review

Questions people ask

Is Dremio or Tinybird better?
Neither clearly leads. Dremio starts at Free and Tinybird at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dremio or Tinybird?
Dremio starts at Free and Tinybird at Free.
Does Dremio or Tinybird run on more platforms?
Dremio runs on Linux, Kubernetes, Cloud, Docker. Tinybird runs on Web, Cloud, Linux, macOS.
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 Tinybird is typically brought in for.
What can Dremio do that Tinybird cannot?
Dremio covers Arrow-based execution, Reflections, Semantic layer, Iceberg catalogue. Tinybird covers Managed ClickHouse, Pipes as APIs, Events HTTP endpoint, Streaming connectors.

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.

Tinybird: Is Tinybird just hosted ClickHouse?

No. The database is ClickHouse, but the product is the layer above it: publishing parameterised SQL as authenticated, rate-limited REST endpoints without writing an API server.

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.

Tinybird: What does it actually cost?

Free tier at 1,000 requests a day, Developer from 25 USD a month, then compute at 0.0002 USD per vCPU-second and storage at 0.058 USD per gigabyte. Higher tiers are quoted.

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.

Tinybird: Can I run it on my own infrastructure?

Only on Enterprise, which offers dedicated infrastructure and private regions. Lower tiers are shared multi-tenant cloud.

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.

Tinybird: Does it handle updates and deletes?

Poorly, as ClickHouse does. Design for append-only event data; frequent mutation is the wrong workload for this engine.

Share

Related pages

More on Dremio

More on Tinybird

Keep looking

Other head to heads