ClickHouse open source analysis
ClickHouse® is a real-time analytics database management system
Project overview
⭐ 45019 · C++ · Last activity on GitHub: 2026-01-05
Why it matters for engineering teams
ClickHouse addresses the need for fast, real-time analytics on large volumes of data, a common challenge in modern software engineering. It is a production ready solution designed to handle analytical queries with high throughput and low latency, making it well suited for machine learning and AI engineering teams who require efficient data processing. Its maturity and reliability have been proven in various production environments, supporting distributed and cloud-native deployments. However, ClickHouse may not be the right choice when transactional consistency and complex relational queries are a priority, as it focuses on analytical workloads rather than transactional processing.
When to use this project
ClickHouse is particularly strong when teams need a self hosted option for real-time analytics on big data with SQL support. Teams should consider alternatives if their use case demands full transactional capabilities or if the workload is primarily OLTP rather than OLAP.
Team fit and typical use cases
Machine learning and AI engineers benefit most from ClickHouse as an open source tool for engineering teams focused on analytics and data science. They typically use it to run fast, complex queries on large datasets that power recommendation systems, anomaly detection, and other AI-driven products. It often appears in data platforms where real-time insights and scalable analytics are essential.
Best suited for
Topics and ecosystem
Activity and freshness
Latest commit on GitHub: 2026-01-05. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.