Metabase
Self-service BI tool for querying and visualising databases.
Core Information
#core_informationName, description, vendor website, logo, technology type and tags.
Overview & Role
Self-service BI tool for querying and visualising databases.
Domain Classification & Tags
Performance Profile
#performance_profileTypical read and write throughput, payload size and processing latency.
Read Performance Profile
Throughput: Highly variable, depends on underlying database and query complexity. Can range from 1-100s of queries/sec for simple dashboards to 0.1-1 query/sec for complex reports.
Payload Size: Highly variable, depends on query results. Can range from KB (e.g., single metric) to MBs (e.g., large tables, detailed reports).
Processing Latency: Highly variable, depends on underlying database and query complexity. Can range from 100s of ms (simple queries) to 10s of seconds or minutes (complex reports on large datasets). Metabase itself adds minimal overhead (tens to hundreds of milliseconds) to the database query time.
Write Performance Profile
Throughput: Not applicable in the traditional sense. Metabase is a read-only BI tool; it does not write data to the underlying databases. Its 'writes' are configuration changes, dashboard saves, or question definitions.
Payload Size: Not applicable. Configuration data is typically small (KB).
Processing Latency: Not applicable. Saving a dashboard or question is typically very fast, in the order of 100-500 ms, as it's just saving metadata to Metabase's internal application database.
Architecture Diagram
#architecture_diagramReference diagram of the technology's internal architecture.
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 Metabase.
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.
Empirical data for standards & compliance is currently being compiled in the global catalog.
Sources
#sourcesDocumentation and research references behind the recorded information.
Empirical data for sources is currently being compiled in the global catalog.
Expert Validation
#expert_validationWhether domain experts reviewed and confirmed the content.
Empirical data for expert validation is currently being compiled in the global catalog.