{"id":"clickhouse-clickhouse-server","name":"clickhouse-server","homepage":"https://hub.docker.com/r/clickhouse/clickhouse-server","repo_url":"https://hub.docker.com/r/clickhouse/clickhouse-server","category":"databases","subcategories":[],"tags":["databases","olap","sql","analytics","columnar","self-hosted"],"what_it_does":"ClickHouse Server is a high-performance columnar database system providing SQL query execution over large datasets. It offers client/server connectivity (typically via native TCP and HTTP interfaces), supports clustering/replication features, and is commonly deployed as a self-managed database service.","use_cases":["Analytics and OLAP workloads (fast aggregations, scans)","Data warehousing and reporting","Log and event analytics pipelines","Real-time dashboards and exploratory SQL over large datasets","ETL/ELT analytical transformations","Time-series and metrics analytics (often with appropriate schema/engines)"],"not_for":["Latency-sensitive transactional workloads (OLTP)","Small-scale embedded use without operational overhead","Use cases requiring built-in managed service SLAs (since this is self-managed software)","Applications that need strict ANSI SQL compatibility without extensions"],"best_when":"You need scalable analytical querying over large volumes with high throughput, and you can operate/manage a database cluster (or a single-node deployment) effectively.","avoid_when":"You require strictly transactional semantics, strong multi-row transactional consistency, or a fully managed turnkey service with guaranteed support and SLAs.","alternatives":["PostgreSQL (general-purpose OLTP/OLAP hybrid)","MySQL / MariaDB","Apache Druid","Apache Pinot","Amazon Redshift","Google BigQuery","Snowflake","Apache Cassandra (for different workload patterns)"],"af_score":39.2,"security_score":51.8,"reliability_score":40.0,"package_type":"mcp_server","discovery_source":["docker_mcp"],"priority":"high","status":"evaluated","version_evaluated":null,"last_evaluated":"2026-03-30T13:34:39.445916+00:00","interface":{"has_rest_api":true,"has_graphql":false,"has_grpc":false,"has_mcp_server":false,"mcp_server_url":null,"has_sdk":false,"sdk_languages":[],"openapi_spec_url":null,"webhooks":false},"auth":{"methods":["Username/password (server-side users/credentials, depending on configuration)","TLS client authentication / certificate-based auth (possible via configuration)","IP allowlists / network-level controls (often used alongside auth)"],"oauth":false,"scopes":false,"notes":"ClickHouse authentication is typically configured at the server/user/role level and depends on the chosen transport (native protocol/HTTP) and security configuration. There is no single standard OAuth-style mechanism across all deployments."},"pricing":{"model":null,"free_tier_exists":false,"free_tier_limits":null,"paid_tiers":[],"requires_credit_card":false,"estimated_workload_costs":null,"notes":"Self-hosted software; costs depend on infrastructure and operational effort rather than per-request pricing."},"requirements":{"requires_signup":false,"requires_credit_card":false,"domain_verification":false,"data_residency":[],"compliance":[],"min_contract":null},"agent_readiness":{"af_score":39.2,"security_score":51.8,"reliability_score":40.0,"mcp_server_quality":0.0,"documentation_accuracy":35.0,"error_message_quality":0.0,"error_message_notes":null,"auth_complexity":55.0,"rate_limit_clarity":20.0,"tls_enforcement":60.0,"auth_strength":60.0,"scope_granularity":40.0,"dependency_hygiene":45.0,"secret_handling":50.0,"security_notes":"Security largely depends on deployment configuration (TLS, network exposure, user/role setup, and access controls). As self-hosted server software, secret handling and transport security are responsibilities of the operator. The ability to scope permissions is present via roles/users, but granularity and scope documentation are not assured from general package-level information.","uptime_documented":0.0,"version_stability":60.0,"breaking_changes_history":55.0,"error_recovery":45.0,"idempotency_support":"false","idempotency_notes":null,"pagination_style":"none","retry_guidance_documented":false,"known_agent_gotchas":["SQL execution is stateful with respect to session settings; agents may need to preserve session-level settings consistently.","Large-result queries can cause memory/network pressure; agents should add LIMITs and appropriate filters.","Schema/engine specifics (e.g., table engines, partitions, distributed tables) affect correctness and performance; agents may generate suboptimal or invalid queries without schema context.","Cluster/replication settings can change which nodes execute queries and how reads/writes behave."]}}