ClickHouse
ClickHouse is an open-source, column-oriented database management system (DBMS) for online analytical processing (OLAP). It is designed for high-performance analytics on large volumes of data, offering incredibly fast query execution and real-time reporting capabilities. Its columnar storage and parallel processing architecture make it highly efficient for analytical workloads.
Core Information
#core_informationName, description, vendor website, logo, technology type and tags.
Overview & Role
ClickHouse is an open-source, column-oriented database management system (DBMS) for online analytical processing (OLAP). It is designed for high-performance analytics on large volumes of data, offering incredibly fast query execution and real-time reporting capabilities. Its columnar storage and parallel processing architecture make it highly efficient for analytical workloads.
Domain Classification & Tags
Performance Profile
#performance_profileTypical read and write throughput, payload size and processing latency.
Read Performance Profile
Throughput: Millions to billions of rows/sec, hundreds of MB/sec to several GB/sec
Payload Size: Varies widely, from single rows (tens of bytes) to large analytical queries returning MBs or GBs of data
Processing Latency: Sub-100 ms for simple queries, hundreds of ms to seconds for complex analytical queries
Write Performance Profile
Throughput: Tens of thousands to hundreds of thousands of rows/sec per core, hundreds of MB/sec to several GB/sec
Payload Size: Typically small rows (tens to hundreds of bytes) in large batches
Processing Latency: Tens of milliseconds for batch commits, sub-second for individual inserts (though batching is preferred)
Architecture Diagram
#architecture_diagramReference diagram of the technology's internal architecture.
Component Architecture & Topology
Features
#featuresCatalogued product capabilities and what each one does.
Empirical data for features is currently being compiled in the global catalog.
Typical Use Cases
#typical_use_casesScenarios the technology is commonly chosen for.
Empirical data for typical use cases is currently being compiled in the global catalog.
Known Customers
#known_customersPublicly referenced organisations using the technology.
Empirical data for known customers is currently being compiled in the global catalog.
Known Integrations
#known_integrationsOther products and services it is documented to work with.
Empirical data for known integrations is currently being compiled in the global catalog.
Connectors
#connectorsDirectional data connections to other technologies, with direction and maturity.
Empirical data for connectors is currently being compiled in the global catalog.
Reference Architectures
#reference_architecturesPublished architectures where the technology is used or mentioned.
No published reference architecture blueprints currently link to ClickHouse.
Security Features
#security_featuresBuilt-in security and access-control capabilities.
Empirical data for security features is currently being compiled in the global catalog.
Known Issues
#known_issuesDocumented limitations, defects and operational pitfalls.
Empirical data for known issues is currently being compiled in the global catalog.
Guidelines
#guidelinesRecommended practices for adopting and operating the technology.
Empirical data for guidelines is currently being compiled in the global catalog.
Standards & Compliance
#standards_and_complianceStandards, certifications and control requirements it maps to.
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Sources
#sourcesDocumentation and research references behind the recorded information.
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Expert Validation
#expert_validationWhether domain experts reviewed and confirmed the content.
Empirical data for expert validation is currently being compiled in the global catalog.