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Software · head to head

ClickHouse vs Dgraph

ClickHouse logo

ClickHouse

Software

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

From
Free
Rated
-
Full reviewWebsite
Dgraph logo

Dgraph

Software

The only native GraphQL database with graph backend

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; Dgraph the GitHub repository (dgraph-io/dgraph) is licensed Apache 2.0 with no paid tier, cloud offering, or enterprise edition mentioned anywhere in the README
  • They diverge on capability: ClickHouse covers Column-oriented Storage, Dgraph covers Native GraphQL.

Where they differ

Only the attributes on which ClickHouse and Dgraph actually diverge.

Attributes where ClickHouse and Dgraph differ
AttributeClickHouseDgraph
Pricing modelUnknownfreemium
PlatformsLinux, macOS, Windows (via Docker)Linux, Mac, Docker, Web
Founded20212016

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

Only in Dgraph

  • Native GraphQL
  • Distributed Architecture
  • ACID Transactions
  • GraphQL Subscriptions
  • Full-text Search
  • Geolocation Queries
  • Horizontal Scaling
  • GraphQL

Both cover

  • Linux support
  • Mac support
  • Docker support
  • Web support

What people use each for

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

ClickHouse

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

Dgraph

  • Knowledge graphsnot ClickHouse
  • Fraud detectionnot ClickHouse
  • Recommendation enginesnot ClickHouse
  • Network analysisnot ClickHouse
  • Master data managementnot 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

Dgraph

  • The GitHub repository (dgraph-io/dgraph) is licensed Apache 2.0 with no paid tier, cloud offering, or enterprise edition mentioned anywhere in the README

Pricing, plan by plan

ClickHouse

Free

No published plan breakdown. See the ClickHouse review.

Dgraph

Free
  • CommunityFree
    • Native GraphQL
    • Graph queries
    • Full-text search
  • Cloud$39/month
    • Managed service
    • Auto-scaling
    • 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 real-time analytics.
ClickHouse review

Choose Dgraph if

  • You need native graphql.
  • You want to start without paying.
  • You work on Linux, Mac, Docker, Web.
  • You also want distributed architecture.
Dgraph review

Questions people ask

Is ClickHouse or Dgraph better?
Neither clearly leads. ClickHouse starts at Free and Dgraph at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ClickHouse or Dgraph?
ClickHouse starts at Free and Dgraph at Free.
Does ClickHouse or Dgraph run on more platforms?
ClickHouse runs on Linux, macOS, Windows (via Docker). Dgraph runs on Linux, Mac, Docker, Web.
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 Dgraph is typically brought in for.
What can ClickHouse do that Dgraph cannot?
ClickHouse covers Column-oriented Storage, Real-time Analytics, SQL Support, Linear Scalability. Dgraph covers Native GraphQL, Distributed Architecture, ACID Transactions, GraphQL Subscriptions. Both handle Linux support, Mac support, Docker support, Web support.

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
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
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
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Related pages

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