Waydev
Code Time
Tower
GitPrime
Screenful Metrics for GitHub
GitClear
Git History
for software developers, teams, and open-source communities

BlueOptima
GitClear
Waydev
CodeClimate
Code Time
GitPrime
LinearB
Developer productivity and engineering analytics from Git changes. Estimate development effort against a consistent baseline, compare developer, team and contractor contributions, and track trends. Cloud, local and on-premises deployment options.

Which is more popular?
Website, pricing, platforms and company facts side by side.
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Git analytics
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|---|---|---|
| Website | gitalytics.com | devghost.pro |
| Pricing | — | |
| Platforms | — | |
| Company | — | Startup from Portugal · 1 - 9 employees · 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.

No description of Git analytics yet.
DevGhost is a developer productivity and engineering analytics platform that helps founders, CTOs, and engineering managers understand work delivered by their teams and development contractors. Git-based effort estimation DevGhost analyzes code changes to estimate development work. Its reference...
What each product offers, as listed by its team.

Possible disadvantages
How often each product is chosen within a category, 0–100% relative to the other.

As answered by people managing Git analytics and DevGhost.pro.
DevGhost.pro's answer:
DevGhost estimates the substantive work behind Git changes using a consistent reference: a mid-level developer who knows the codebase and works without AI. This makes contributions comparable beyond commit counts and lines of code. Teams can explore individual output, repository-wide trends, and changes in productivity as development workflows evolve. DevGhost also offers fully local analysis: both code processing and analytics run on your machine, with source code and results staying local.
DevGhost.pro's answer:
Choose DevGhost when you need to understand the work delivered by a development team or contractor and compare contributions on a shared scale. It combines effort estimates, developer breakdowns, and productivity timelines in an interactive report. This helps founders and engineering leaders connect progress discussions to actual code changes. With cloud, local, and on-premises options, you can choose a deployment model that fits your workflow and confidentiality requirements.
DevGhost.pro's answer:
DevGhost is built for founders, CTOs, engineering managers, and product owners who need visibility into software development. It is especially useful for organizations working with outsourced development teams, agencies, or freelancers, and for leaders trying to understand how AI-assisted development is changing their team's output.
DevGhost.pro's answer:
DevGhost is built around a simple question: how much substantive work is actually being delivered? Busy teams, frequent commits, and detailed status reports do not always make that clear. AI-assisted development makes the question even more important, as one developer's output can change dramatically. DevGhost brings code changes onto a common reference scale so founders and engineering leaders can see contributions, follow trends, and have more concrete conversations about delivery.
DevGhost.pro's answer:
We do not publish customer names. Engineering productivity and team contribution data can be sensitive, particularly when it involves individual developers or external contractors. We respect the confidentiality of these assessments and the reputations of the people and organizations involved.
DevGhost.pro's answer:
DevGhost is built with TypeScript, React, Next.js, and Node.js. Its Python analysis engine uses Git, Tree-sitter, NumPy, and scikit-learn to process and analyze code changes. The web platform uses PostgreSQL with Prisma, while the local edition uses SQLite. The VS Code and Cursor extension combines TypeScript with React-based webviews. The Windows desktop application is built with Electron and shares the local analysis engine. Cloud and on-premises deployment options are supported through Modal and Docker-based infrastructure.
Share your experience with using Git analytics and DevGhost.pro. For example, how are they different and which one is better?
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