Is Definite a data warehouse for my GitHub data?

Yes. Definite is your complete data warehouse for GitHub data—no need to pay for Snowflake, BigQuery, or Databricks. Definite syncs your data into secure, managed infrastructure, powered by DuckDB for high-performance analytics. Definite handles encrypted, persistent storage behind the scenes with enterprise-grade security, automatic syncing, and backups. You get lightning-fast queries, built-in business intelligence tools, and SOC 2–compliant data residency options—all without the overhead or complexity of running a separate warehouse.

Can I analyze my GitHub data with other data sources?

Yes. Definite lets you connect and analyze data across all your tools — from app databases and CRMs to marketing automation, analytics, and customer support platforms. Our built-in Sync Engine supports over 500+ data sources, with options for daily, hourly, or near real-time. Definite makes analysis easy. You can select metrics and dimensions from your GitHub data alongside other sources to explore insights, build dashboards, and share results — no SQL needed (unless you want to). Or simply ask Fi, our AI analyst, to find answers, uncover patterns, and instantly create charts and reports for you.

Can Definite connect GitHub data to tools like Python, SQL, Google Sheets, or Slack?

Yes. Definite integrates seamlessly with the tools you already use. You can run Python scripts for advanced analysis, query your data directly with SQL, or sync results to Google Sheets and Slack for easy sharing. Data can be exported in CSV, Excel, or JSON, accessed via the Metrics API, or embedded directly into your product or internal dashboards. Definite makes it simple to connect, automate, and share insights wherever your team works.

How does Definite's AI actually work?

Definite includes Fi, our AI data analyst that understands your business data and speaks your language. Fi can explore your connected sources, write SQL, and build charts or dashboards in minutes — turning plain-English questions into real analysis. Under the hood, Fi uses Definite's semantic models and query engine to interpret context, generate accurate queries, and explain results clearly. The result: faster insights, fewer bottlenecks, and analytics that finally deliver ROI.

Can I use Definite for free?

Yes. Definite offers a free plan for qualifying startups that includes core analytics, dashboards, and AI insights — everything you need to get started. You can upgrade anytime for more data sources, faster syncs, and advanced automations.

Explore with AI

← All connectors/Development

§ Connector

GitHub

Analyze your GitHub data with AI today.

Build dashboards, automate reports, and ask questions in plain English — all from your GitHub data, no complex infrastructure to maintain.

Start analyzing GitHub →Book a demo

Have multiple GitHub accounts? Analytics across multiple GitHub accounts →

§ Live with

§ What you get

Everything GitHub exposes, modeled and queryable.

Extracts rich GitHub data across repositories, organizations, and users. It covers repository metadata, commits, issues, pull requests, comments and reviews, releases, labels, branches, tags, collaborators, contributors and stargazers, discussions, dependency graph, Actions workflows and runs, deployments, traffic analytics, and organization teams and members. This enables engineering analytics (velocity, quality, code review and CI/CD health), community and engagement tracking (stars, discussions, contributors), dependency risk insights, and organizational visibility (projects, teams, roles). Uses both REST and GraphQL APIs, plus limited HTML scraping for dependents and extra metrics.

Standard on every Definite connector

Sync cadence

Hourly or faster

CDC

Native where supported

Auth

OAuth / API key

Row-level security

Yes

Tables & streams

16 objects

◆Organization

A GitHub organization and its portfolio of repositories and members; enables org-level analytics like repo coverage, membership growth, and team structure for ownership and access insights.

◆Team

A team within an organization used to group people and ownership; supports attribution of work and activity by team, coverage of critical repos, and cross-team collaboration analysis.

◆Repository

A code project with metadata and governance; powers repository-level KPIs such as activity and health, language composition, branch/tag hygiene, and community readiness (README and community files).

◆Dependency

Inventory of dependencies a repository uses and dependents that rely on it; enables supply-chain risk, upgrade cadence, and adoption/impact analysis across the ecosystem.

◆Contributor

People and bots contributing code to a repository; supports engineering throughput, concentration of contribution, and code churn analysis over time.

◆Stargazer

Users who star repositories and the time they starred; used to measure community interest, growth trends, and cohort analyses of star acquisition.

◆Repository Traffic

Views, clones, top referrers, and popular paths for a repository; enables engagement and discovery analytics to understand audience, content performance, and traffic drivers.

◆Issue

Work items and bug reports (including PRs as issues) with comments and events; supports backlog health, response SLAs, triage effectiveness, and time-to-close metrics with label/assignee segmentation.

◆Pull Request

Code change proposals with commits, reviews, and review comments; enables lead time for changes, review efficiency, approval rates, merge velocity, and PR size/complexity analysis.

◆Commit

Individual code changes with authorship and diffs; used to measure delivery throughput, commit cadence, and code churn (additions/deletions) by author, team, or branch.

◆Release

Versioned releases and assets; supports release cadence, time between releases, and mapping of changes from tags to released artifacts.

◆Milestone

Time-bound goals grouping issues and PRs; enables roadmap tracking, burn-down, completion rates, and schedule risk assessment.

◆Workflow Run (GitHub Actions)

CI/CD workflows, runs, and jobs with step timings; powers build success rates, flakiness, failure causes, and run/step duration trends.

◆Deployment

Deployments and their statuses across environments; enables DORA metrics like deployment frequency, change failure rate, and MTTR via status outcomes and timestamps.

◆Discussion

Threaded discussions with categories, comments, replies, and reactions; supports community engagement analysis, answer rates, and sentiment on topics.

◆Project (Projects V2)

Project boards and items with configurable fields; used for cross-repo planning, WIP limits, cycle/lead time, and progress tracking across teams.

Authentication

Uses a GitHub personal access token or a GitHub App key to authenticate (short‑lived installation tokens supported with automatic rotation for rate limits)

Requirements

Requires a GitHub account to connect.

Analyze with Fi

Operational data, performance metrics, and business insights.

§ How it works