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ClickHouse vs TiDB

ClickHouse logo

ClickHouse

Software

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

From
Free
Rated
-
Full reviewWebsite
TiDB logo

TiDB

Software

Open source distributed HTAP database for elastic scale and real-time analytics

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; TiDB not 100% MySQL-compatible, requiring verification before migration
  • They diverge on capability: ClickHouse covers Column-oriented Storage, TiDB covers MySQL Compatible.

Where they differ

Only the attributes on which ClickHouse and TiDB actually diverge.

Attributes where ClickHouse and TiDB differ
AttributeClickHouseTiDB
Pricing modelUnknownfreemium
PlatformsLinux, macOS, Windows (via Docker)Cloud, AWS, Azure, Google Cloud Platform, Self-managed
Founded20212015

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).

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
  • SQL Support
  • Linear Scalability
  • Data Compression
  • Vectorized Query Execution
  • Approximate Calculations
  • S3
  • PostgreSQL

Only in TiDB

  • MySQL Compatible
  • HTAP Workloads
  • Horizontal Scaling
  • Strong Consistency
  • High Availability
  • Elastic Scaling
  • Spark
  • Prometheus

Both cover

  • Real-time Analytics
  • Kafka
  • MySQL
  • Grafana
  • Linux support
  • Docker support
  • Kubernetes support
  • Web support

What people use each for

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

ClickHouse

  • Business intelligencenot TiDB
  • Data warehousingnot TiDB
  • Real-time analyticsnot TiDB
  • Reporting
  • Machine learningnot TiDB

TiDB

  • Transaction processingnot ClickHouse
  • Data storagenot ClickHouse
  • Application backendnot ClickHouse
  • Reporting
  • Data analyticsnot ClickHouse

Both are used for reporting, on those jobs the choice comes down to price and fit rather than capability.

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

TiDB

  • Not 100% MySQL-compatible, requiring verification before migration

Pricing, plan by plan

ClickHouse

Free

No published plan breakdown. See the ClickHouse review.

TiDB

Free
  • ServerlessFree
    • 5GB storage
    • 50M request units
    • Free forever tier
  • Dedicated$250/month
    • Dedicated resources
    • SLA guarantees
    • Enterprise support

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 sql support.
ClickHouse review

Choose TiDB if

  • You need mysql compatible.
  • You want to start without paying.
  • You work on Cloud, AWS, Azure, Google Cloud Platform, Self-managed.
  • You also want htap workloads.
TiDB review

Questions people ask

Is ClickHouse or TiDB better?
Neither clearly leads. ClickHouse starts at Free and TiDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ClickHouse or TiDB?
ClickHouse starts at Free and TiDB at Free.
Does ClickHouse or TiDB run on more platforms?
ClickHouse runs on Linux, macOS, Windows (via Docker). TiDB runs on Cloud, AWS, Azure, Google Cloud Platform, Self-managed.
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 TiDB is typically brought in for.
What can ClickHouse do that TiDB cannot?
ClickHouse covers Column-oriented Storage, SQL Support, Linear Scalability, Data Compression. TiDB covers MySQL Compatible, HTAP Workloads, Horizontal Scaling, Strong Consistency. Both handle Real-time Analytics, Kafka, MySQL, Grafana.

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
TiDB: Is TiDB MySQL-compatible?

Yes, TiDB speaks the MySQL protocol, so existing MySQL clients, ORMs, and drivers work without modification. However, TiDB is not 100% MySQL-compatible.

Source
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
TiDB: How does TiDB scale?

TiDB provides automatic horizontal scaling with compute and storage scaling independently. It splits compute (TiDB servers) from storage (TiKV) to allow adding nodes without data replication.

Source
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
TiDB: Does TiDB support analytics workloads?

Yes, TiDB is an HTAP database with TiFlash columnar engine providing analytics capabilities alongside transactional processing on the same data without separate pipelines.

Source
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