spb/tools-spboucher-ai
Public
1{2 "aliases": [3 "chDB",4 "clickhouse-local"5 ],6 "workflows": [7 "Store and aggregate tick or minute-bar data across years",8 "Log and trace analytics behind Grafana dashboards",9 "Query Parquet files on S3 directly with table functions",10 "Serve product analytics dashboards from Metabase or Superset"11 ],12 "advantages": [13 "Very fast analytical scans on a single node",14 "Apache 2.0 and self-hostable",15 "Broad format and external-source support",16 "Managed cloud option"17 ],18 "limitations": [19 "Updates and deletes are asynchronous mutations",20 "No OLTP-style transactions",21 "Large joins are memory-intensive",22 "Dialect differences from standard PostgreSQL SQL"23 ],24 "prerequisites": [25 "A Linux server, Docker or macOS binary, or a ClickHouse Cloud account"26 ],27 "audiences": [28 "Data engineers",29 "Observability and product-analytics teams",30 "Quantitative researchers with large time series"31 ],32 "alternatives": [33 "duckdb",34 "apache-spark",35 "trino",36 "timescaledb",37 "elasticsearch",38 "postgresql"39 ],40 "tags": [41 "olap",42 "columnar",43 "sql",44 "time-series",45 "parquet",46 "open-source",47 "self-hosted",48 "monitoring"49 ],50 "use_cases": [51 "analyze-intraday-data",52 "query-parquet-files",53 "monitor-services"54 ],55 "operating_systems": [56 "linux",57 "macos"58 ],59 "deployment_models": [60 "on-premises",61 "managed-cloud",62 "embedded"63 ],64 "integrations": [65 "Grafana",66 "Metabase",67 "Apache Superset",68 "Apache Kafka",69 "dbt",70 "Amazon S3",71 "PostgreSQL",72 "MySQL",73 "Apache Iceberg"74 ],75 "data_formats": [76 "Parquet",77 "CSV",78 "TSV",79 "JSON",80 "Arrow",81 "ORC",82 "Avro",83 "Native"84 ],85 "languages": [86 "C++",87 "SQL",88 "Python",89 "Go",90 "Java",91 "JavaScript",92 "Rust",93 "C#"94 ],95 "self_hostable": true,96 "discovery_method": "editorial-research",97 "depth": "deep",98 "editorial_status": "reviewed",99 "visibility": "public",100 "featured": false,101 "author": "batch-D",102 "slug": "clickhouse",103 "name": "ClickHouse",104 "vendor": {105 "name": "ClickHouse, Inc.",106 "slug": "clickhouse-inc",107 "website": "https://clickhouse.com/"108 },109 "homepage_url": "https://clickhouse.com/",110 "docs_url": "https://clickhouse.com/docs",111 "repo_url": "https://github.com/ClickHouse/ClickHouse",112 "license_url": "https://github.com/ClickHouse/ClickHouse/blob/master/LICENSE",113 "pricing_url": "https://clickhouse.com/pricing",114 "pricing_checked_at": "2026-11-02",115 "product_type": "database",116 "product_status": "active",117 "summary": "Open-source columnar OLAP database server for fast aggregations over billions of rows, with MergeTree storage, SQL and a managed ClickHouse Cloud",118 "description": "ClickHouse is an open-source column-oriented database management system developed by ClickHouse, Inc. under Apache 2.0, originally built at Yandex for web analytics. Its MergeTree family of table engines stores sorted, compressed column parts with sparse primary indexes and skipping indexes, and the vectorized SQL engine aggregates billions of rows per second on a single server, with distributed tables, replication via ClickHouse Keeper and sharding for clusters. Beyond native tables it queries external data through table functions for S3, HTTP, PostgreSQL, MySQL, Kafka and files in Parquet, CSV, JSON and dozens of other formats, and materialized views transform data on insert. clickhouse-local runs the same engine from the command line over local files, and chDB embeds it in Python, Node, Go and Rust processes.\n\nTypical workloads are event analytics, observability (logs, traces, metrics), time-series and financial tick data, and serving dashboards from Grafana, Metabase or Superset over HTTP or the native protocol with clients in most languages. ClickHouse Cloud is the managed service with separated storage and compute; many teams self-host a single node on Linux or in Docker, including on Apple Silicon.\n\nThe design optimizes append-heavy, read-mostly analytics: updates and deletes run as asynchronous mutations, there are no multi-statement transactions in the OLTP sense, joins of large tables need memory and care, and the SQL dialect has its own functions and behaviors that differ from PostgreSQL. Small point lookups and frequent single-row inserts should be batched or routed elsewhere.",119 "capabilities": [120 "Columnar MergeTree storage with compression and sparse indexes",121 "Vectorized SQL execution with parallel aggregation",122 "Replication and sharding via ClickHouse Keeper and distributed tables",123 "Table functions for S3, HTTP, PostgreSQL, MySQL, Kafka and local files",124 "Materialized views and projections for on-insert transformation",125 "Reads and writes Parquet, CSV, JSON, Arrow and many other formats",126 "clickhouse-local CLI and chDB embedded engine",127 "HTTP and native protocol clients for Python, Go, Java, JavaScript, Rust and more"128 ],129 "comparison_notes": "DuckDB offers a similar columnar, vectorized engine but in-process and single-user, whereas ClickHouse is a networked server with replication and sharding. Spark and Trino are distributed query engines over external storage rather than storage engines themselves. TimescaleDB keeps time-series data inside PostgreSQL with full transactions at lower scan speed. Elasticsearch addresses log analytics through inverted indexes and a JSON DSL instead of columnar SQL.",130 "categories": [131 {132 "slug": "analytics-engines",133 "primary": true134 },135 {136 "slug": "relational-databases"137 },138 {139 "slug": "hf-finance-research",140 "label": "Server-side store for large tick archives"141 }142 ],143 "execution_modes": [144 "self-hosted",145 "cloud",146 "local"147 ],148 "interfaces": [149 "cli",150 "api",151 "library",152 "sdk"153 ],154 "source_model": "open-source",155 "license_spdx": "Apache-2.0",156 "pricing_model": [157 "open-source",158 "free",159 "usage-based",160 "enterprise"161 ],162 "sources": [163 {164 "url": "https://clickhouse.com/",165 "type": "official_site",166 "supports": [167 "name",168 "summary",169 "vendor"170 ],171 "checked_at": "2026-11-02",172 "title": "ClickHouse"173 },174 {175 "url": "https://clickhouse.com/docs",176 "type": "official_docs",177 "supports": [178 "capabilities",179 "data_formats",180 "languages"181 ],182 "checked_at": "2026-11-02",183 "title": "ClickHouse Docs"184 },185 {186 "url": "https://github.com/ClickHouse/ClickHouse/blob/master/LICENSE",187 "type": "license_page",188 "supports": [189 "license_spdx",190 "source_model"191 ],192 "checked_at": "2026-11-02",193 "title": "ClickHouse LICENSE (Apache 2.0)"194 },195 {196 "url": "https://clickhouse.com/pricing",197 "type": "pricing_page",198 "supports": [199 "pricing_model"200 ],201 "checked_at": "2026-11-02",202 "title": "ClickHouse Cloud pricing"203 },204 {205 "url": "https://github.com/ClickHouse/ClickHouse",206 "type": "repository",207 "supports": [208 "repo_url"209 ],210 "checked_at": "2026-11-02",211 "title": "ClickHouse/ClickHouse"212 }213 ],214 "confidence": "high"215}216