ClickHouse
An open-source column-oriented OLAP database management system supporting a vectorized execution engine, capable of sub-second aggregation queries across trillions of rows. It is commonly used for large-scale web crawl data storage and analysis.
Timeline (last 90 days)
A Postgres conference talk compiled by ClickHouse put forward the view that "Postgres is not slow, your storage is slow," arguing that many complaints about Postgres performance are rooted in the configuration and selection of the underlying storage layer.
Claude Dashboards directly connects to six types of data sources: BigQuery, Databricks, Snowflake, Redshift, ClickHouse, and Salesforce.
Companies such as ByteDance and Cloudflare use ClickHouse for internal log and user behavior analysis.
ClickHouse supports vectorized execution and data compression, maintaining second-level response times when processing tens of billions of rows of data on a single machine.
ClickHouse was open-sourced by Russian company Yandex in 2016 and is designed specifically for OLAP (Online Analytical Processing) scenarios.
Columnar storage can deliver performance improvements of tens of times over traditional row-based databases for aggregation operations, because queries only read the involved columns rather than entire rows.
The author built a ClickHouse database that allows users to query online, with database credentials available via direct message.
In self-hosted Sentry, ClickHouse handles high-speed writing and querying of event data, while Kafka provides buffering and traffic shaping at the data ingestion layer.
The primary method for self-hosting Sentry is the officially maintained self-hosted repository, which relies on Docker Compose to orchestrate a service stack comprising components such as PostgreSQL, Redis, Kafka, and ClickHouse.
Mainstream data systems such as Elasticsearch, ClickHouse, and MongoDB have successively added vector index support.
19 more timeline events
All Facts (20)
A Postgres conference talk compiled by ClickHouse put forward the view that "Postgres is not slow, your storage is slow," arguing that many complaints about Postgres performance are rooted in the configuration and selection of the underlying storage layer.
50%UnverifiedClaude Dashboards directly connects to six types of data sources: BigQuery, Databricks, Snowflake, Redshift, ClickHouse, and Salesforce.
50%UnverifiedCompanies such as ByteDance and Cloudflare use ClickHouse for internal log and user behavior analysis.
50%UnverifiedClickHouse supports vectorized execution and data compression, maintaining second-level response times when processing tens of billions of rows of data on a single machine.
50%UnverifiedClickHouse was open-sourced by Russian company Yandex in 2016 and is designed specifically for OLAP (Online Analytical Processing) scenarios.
50%UnverifiedColumnar storage can deliver performance improvements of tens of times over traditional row-based databases for aggregation operations, because queries only read the involved columns rather than entire rows.
50%UnverifiedThe author built a ClickHouse database that allows users to query online, with database credentials available via direct message.
50%UnverifiedIn self-hosted Sentry, ClickHouse handles high-speed writing and querying of event data, while Kafka provides buffering and traffic shaping at the data ingestion layer.
50%UnverifiedThe primary method for self-hosting Sentry is the officially maintained self-hosted repository, which relies on Docker Compose to orchestrate a service stack comprising components such as PostgreSQL, Redis, Kafka, and ClickHouse.
50%UnverifiedMainstream data systems such as Elasticsearch, ClickHouse, and MongoDB have successively added vector index support.
50%UnverifiedAccording to official public benchmark tests, SereneDB outperforms Elasticsearch, ClickHouse, and Postgres search extensions in full-text search and analytics scenarios.
50%UnverifiedIn a dual-system architecture, ETL pipelines are typically required to synchronize data between full-text search and analytical query systems, introducing data latency and consistency issues.
50%UnverifiedDatabases such as DuckDB and ClickHouse have trended toward "storage-compute separation" in recent years.
50%UnverifiedClickHouse uses agents to fix flaky tests and find missing test coverage, and the agents have become the second and third largest contributors to its repository.
50%UnverifiedClickHouse delivered 30% more features using Claude Code.
50%UnverifiedClickHouse directly uses Claude Code to build and iterate on the SQL Agent and AI SRE used by customers.
50%UnverifiedClickHouse's primary key index records an index mark every 8192 rows (the default index_granularity), adopting a sparse index design.
50%UnverifiedThe compression ratio of columnar storage is typically between 10:1 and 100:1, because data in the same column has a consistent type and similar value distribution.
50%UnverifiedClickHouse is a high-performance columnar analytical database that uses a columnar storage architecture where data is organized on disk by column rather than by row.
50%UnverifiedClickHouse provides role-based access control (RBAC) and column-level GRANT mechanisms, but lacks native row-level security policies.
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