ClickHouse Columnar Analytics Database

ClickHouse is a column-oriented database management system purpose-built for online analytical processing, capable of running millisecond queries over petabyte-scale datasets and powering agentic AI systems at companies including Anthropic for Claude, Tesla for vehicle telemetry, Lyft for ride analytics, Cisco, GitLab, Spotify, eBay, Microsoft, Meta, Cloudflare, and Vercel. The columnar storage engine processes analytical queries 100 times faster than traditional row-oriented databases by reading only the columns referenced in a query, compressing data at ratios of 5:1 to 10:1 using LZ4 and ZSTD codecs, and vectorizing execution through SIMD instructions. Over 100 thousand developers use the platform, backed by 48.2 thousand GitHub stars, 2.9 thousand contributors, 77.9 thousand pull requests, and 799 releases. The ClickStack observability stack combines the database with Grafana dashboards, OpenTelemetry collectors, and log ingestion to replace Datadog and Splunk at a fraction of the cost. The managed ClickHouse Cloud runs on AWS, GCP, and Azure with serverless auto-scaling, separating compute and storage with S3-compatible object storage backends. ClickHouse Local enables querying local and remote files in formats including Parquet, CSV, JSON, Arrow, and ORC directly from the command line without a server. The chDB embedded engine provides in-process analytical query execution for Python and Node.js applications without network overhead. ClickPipes handles continuous data ingestion from Kafka, Kinesis, S3, PostgreSQL CDC, and 100 plus integration partners including Airbyte, dbt, Fivetran, Grafana, Metabase, and Superset. The query language extends SQL with approximated analytics functions, array operations, JSON extraction, machine learning models, and vector similarity search for embedding-based retrieval. Langfuse LLM observability is now integrated as part of the platform.