{"id":"clickhouse-api","name":"ClickHouse","homepage":"https://clickhouse.com","repo_url":"https://github.com/ClickHouse/ClickHouse","category":"database","subcategories":["olap","analytics-database","columnar","time-series","cloud-database"],"tags":["clickhouse","olap","analytics","columnar","time-series","event-analytics","http-interface","sql","open-source","cloud-database","log-analytics"],"what_it_does":"ClickHouse is a blazing-fast open-source columnar OLAP database designed for real-time analytics over massive datasets. It stores data in column-oriented format with aggressive compression, enabling queries that scan billions of rows per second. ClickHouse accepts SQL via an HTTP interface (port 8123/8443) and a native binary protocol (port 9440), with support for many input/output formats (JSON, CSV, Parquet, Arrow). ClickHouse Cloud is the managed offering with a REST Management API for programmatic cluster management. The HTTP interface supports streaming responses, progress headers, and session-based queries — making it well-suited for agents that need to run complex analytical queries.","use_cases":["Sub-second analytical queries over billions of rows of event, log, or telemetry data","Real-time dashboards and alerting over streaming event data ingested at millions of events/second","Product analytics and user behavior analysis with complex funnel and session queries","Log analytics and observability data storage with time-based partitioning and TTL policies","Programmatic ClickHouse Cloud service provisioning and scaling via Management API","Data warehouse queries using S3-backed external table integrations (ClickHouse reads directly from S3/GCS)"],"not_for":["OLTP transactional workloads requiring row-level updates, foreign keys, or ACID across multiple tables (use PostgreSQL or MySQL)","Frequent point updates — ClickHouse is append-optimized; mutations (UPDATE/DELETE) are slow and asynchronous","Small datasets where simpler tools (PostgreSQL, SQLite) suffice — ClickHouse has significant setup overhead","Teams needing simple SQL without understanding columnar database concepts like MergeTree engine families"],"best_when":"You need to run fast analytical queries over large volumes of immutable or append-only event/log data, especially when time-series patterns, aggregations over billions of rows, or real-time ingestion are requirements.","avoid_when":"You need frequent row-level updates, complex multi-table transactions, or a general-purpose OLTP database.","alternatives":[{"id":"elasticsearch-api","reason":"Elasticsearch is better for full-text search and log exploration; ClickHouse is faster for pure aggregation analytics"},{"id":"neon-api","reason":"Neon/PostgreSQL better for OLTP workloads requiring transactions and updates"},{"id":"bigquery-api","reason":"BigQuery is better for ad-hoc serverless analytics on petabyte-scale datasets in GCP"}],"af_score":67.0,"security_score":80.0,"reliability_score":null,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":"current","last_evaluated":"2026-03-01T09:50:05.388971+00:00","performance":{"latency_p50_ms":2,"latency_p99_ms":50,"uptime_sla_percent":99.99,"rate_limits":"No hard rate limits on self-hosted; ClickHouse Cloud scales with cluster configuration. Concurrent query limits configurable per user.","data_source":"llm_estimated","measured_on":null}}