How GitLab uses ClickHouse to scale analytical workloads

GitLab's transition to ClickHouse for analytics has significantly enhanced its ability to handle massive data scales and deliver near-instant insights, transforming its analytics infrastructure into a real-time, scalable platform. Initially using Postgres for both transactional and analytical workloads, GitLab recognized the need for a specialized analytics solution as the demand for real-time, scalable user-facing analytics grew. ClickHouse emerged as the optimal choice due to its superior performance, scalability, and ease of deployment, supporting GitLab’s architectural requirements and handling large data volumes efficiently. This shift allowed GitLab to overcome previous performance bottlenecks, with queries that once took 30-40 seconds now resolving in under a second. By integrating ClickHouse, GitLab has improved features such as Contribution Analytics and SDLC trends, enabling advanced insights into engineering outcomes and AI adoption. The transition has also been strategically aligned with GitLab's broader move towards an event-driven, analytics-first platform, leveraging ClickHouse's capabilities for a seamless and scalable analytics experience across its SaaS, on-premise, and self-managed environments.

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