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Databases · head to head

ClickHouse vs Tinybird

ClickHouse logo

ClickHouse

Databases

Fast open-source column-oriented database for real-time analytics

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: ClickHouse limited multi-row atomic transactions and expensive UPDATE/DELETE operations unsuitable for transactional systems; 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: ClickHouse covers Column-oriented Storage, Tinybird covers Managed ClickHouse.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which ClickHouse and Tinybird actually diverge.

Attributes where ClickHouse and Tinybird differ
AttributeClickHouseTinybird
Pricing modelUnknownPer month by compute and storage
PlatformsLinux, macOS, Windows (via Docker)Web, Cloud, Linux, macOS
Founded2021Unknown

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 ClickHouse

  • Column-oriented Storage
  • Real-time Analytics
  • SQL Support
  • Linear Scalability
  • Data Compression
  • Vectorized Query Execution
  • Approximate Calculations
  • Kafka

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.

ClickHouse

  • Business intelligencenot Tinybird
  • Data warehousingnot Tinybird
  • Real-time analyticsnot Tinybird
  • Reportingnot Tinybird
  • Machine learningnot Tinybird

Tinybird

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

Where each one falls short

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

ClickHouse

  • Limited multi-row atomic transactions and expensive UPDATE/DELETE operations unsuitable for transactional systems
  • Requires upfront schema design discipline with MergeTree engine choices and sort/partition keys
  • Experimental vector search support, not production-ready for vector operations
  • Different query syntax from standard SQL requiring migration planning
  • Limited JOIN capabilities compared to traditional relational databases
  • Migration complexity with 2-4 weeks estimated for data type mapping and query translation

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

ClickHouse

Free

No published plan breakdown. See the ClickHouse review.

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 ClickHouse if

  • You need column-oriented storage.
  • You want to start without paying.
  • You work on Linux, macOS, Windows (via Docker).
  • You also want real-time analytics.
ClickHouse 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 ClickHouse or Tinybird better?
Neither clearly leads. ClickHouse 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, ClickHouse or Tinybird?
ClickHouse starts at Free and Tinybird at Free.
Does ClickHouse or Tinybird run on more platforms?
ClickHouse runs on Linux, macOS, Windows (via Docker). Tinybird runs on Web, Cloud, Linux, macOS.
Can I use ClickHouse for free?
Both have a free tier, so you can try either at no cost before committing.
What is ClickHouse best used for?
ClickHouse is most often used for business intelligence, data warehousing, real-time analytics, reporting. Of those, business intelligence and data warehousing are not what Tinybird is typically brought in for.
What can ClickHouse do that Tinybird cannot?
ClickHouse covers Column-oriented Storage, Real-time Analytics, SQL Support, Linear Scalability. Tinybird covers Managed ClickHouse, Pipes as APIs, Events HTTP endpoint, Streaming connectors.

Answered from the vendors’ own pages

ClickHouse: What is ClickHouse best used for?

ClickHouse is optimized for analytical workloads on large datasets. It excels at fast aggregations and queries, being 10-100x faster than PostgreSQL on large aggregations.

Source
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.

ClickHouse: Does ClickHouse support transactions?

ClickHouse has limited transaction support and expensive UPDATE/DELETE operations. It is not suitable for transactional workloads requiring strict ACID guarantees.

Source
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.

ClickHouse: How does ClickHouse compare to PostgreSQL?

ClickHouse is 10-100x faster for analytics but PostgreSQL is better for transactional workloads. Many teams use both: PostgreSQL for writes via MaterializedPostgreSQL replication to ClickHouse for analytics.

Source
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.

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.

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