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Database & Data Management · head to head

ClickHouse vs Qdrant

ClickHouse logo

ClickHouse

Database & Data Management

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

From
Free
Rated
-
Full reviewWebsite
Qdrant logo

Qdrant

Database & Data Management

High-performance vector database for similarity search and embedding-based retrieval

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; Qdrant free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments

Where they differ

Only the attributes on which ClickHouse and Qdrant actually diverge.

Attributes where ClickHouse and Qdrant differ
AttributeClickHouseQdrant
Pricing modelUnknownfreemium
PlatformsLinux, macOS, Windows (via Docker)Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming)
Founded2021Unknown

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

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 Qdrant

Nothing recorded that ClickHouse does not also cover.

What people use each for

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

ClickHouse

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

Qdrant

  • Retrieval-augmented generation (RAG) backends for LLM applicationsnot ClickHouse
  • Semantic search across large document corporanot ClickHouse
  • Multimodal retrieval (text, images, video) for recommendation systemsnot ClickHouse
  • Similarity-based product or content recommendationsnot ClickHouse
  • Real-time vector indexing for streaming embedding datanot 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

Qdrant

  • Free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments
  • Standard and Premium pricing usage-based; specific costs not published; requires calculator or quote
  • Requires understanding of embeddings and vector search concepts; not suitable for SQL-only teams
  • Early-stage serverless offering (coming soon) suggests maturity gaps in that deployment model

Pricing, plan by plan

ClickHouse

Free

No published plan breakdown. See the ClickHouse review.

Qdrant

Free
  • FreeFree
    • Single-node cluster
    • 0.5 vCPU
    • 1GB RAM
  • Standard$null/usage-based
    • Dedicated resources
    • Flexible scaling
    • High availability
  • Premium$null/minimum spend
    • SSO and SAML
    • Private VPC links
    • 99.9% uptime SLA

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 Qdrant if

  • You want to start without paying.
  • You work on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming).
Qdrant review

Questions people ask

Is ClickHouse or Qdrant better?
Neither clearly leads. ClickHouse starts at Free and Qdrant at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ClickHouse or Qdrant?
ClickHouse starts at Free and Qdrant at Free.
Does ClickHouse or Qdrant run on more platforms?
ClickHouse runs on Linux, macOS, Windows (via Docker). Qdrant runs on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming).
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 Qdrant is typically brought in for.
What can ClickHouse do that Qdrant cannot?
ClickHouse covers Column-oriented Storage, Real-time Analytics, SQL Support, Linear Scalability.

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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