Query your engineering data with the power of SQL to drive DevOps excellence.
MergeStat is a high-performance Software Engineering Intelligence (SEI) platform designed to bridge the gap between git-based workflows and relational data analysis. By architecting a sophisticated synchronization engine that maps complex Git metadata—including commits, pull requests, issues, and file-level history—into a structured PostgreSQL schema, MergeStat enables engineering leaders to treat their entire codebase as a queryable database. Its 2026 market position is defined by its hybrid approach: providing an open-source core for local auditing while offering a robust Cloud SaaS for enterprise-wide DORA metrics and security compliance. The technical stack leverages custom Postgres Foreign Data Wrappers (FDW) and high-concurrency workers to ingest data from GitHub, GitLab, and Bitbucket. This allows for real-time visibility into developer velocity, code churn, and security posture without the overhead of manual reporting. For the modern CTO, MergeStat serves as a single source of truth for quantitative engineering performance, facilitating data-driven decisions on resource allocation and technical debt remediation.
Uses a custom FDW to query external APIs (GitHub/GitLab) directly from the SQL engine without pre-syncing for light lookups.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Visual documentation of the unified schema mapping across different VCS providers.
SQL views optimized for calculating Lead Time for Changes, Deployment Frequency, MTTR, and Change Failure Rate.
Runs secret-scanning as a table function during the ingestion process.
Calculates the ratio of lines added to lines deleted/modified over time across specific directories.
Stores stateful snapshots of PR and Issue statuses for historical trend analysis.
Allows embedding of Metabase dashboards directly within the MergeStat UI.
Manual evidence collection for pull request approvals is time-consuming and prone to error.
Registry Updated:2/7/2026
Identifying which parts of a microservices architecture are no longer being maintained.
Quantifying where high-churn files correlate with high bug report rates.