
Google App Engine
Salesforce Platform
AWS Lambda
Dokku
Azure Web Apps
AWS Elastic Beanstalk
Azure Functions
A serverless platform for building event-based microservices.

BlueOptima
GitClear
Waydev
CodeClimate
Code Time
Git analytics
GitPrime
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?
Based on our record, Google Cloud Functions seems to be more popular. It has been mentioned 52 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | cloud.google.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 Google Cloud Functions 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
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
No analysis of DevGhost.pro yet.
Walkthroughs and reviews on video.
Google Cloud Functions: introduction to event-driven serverless compute on GCP
More videos
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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing Google Cloud Functions 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 Google Cloud Functions and DevGhost.pro. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


Google Cloud Functions is a natural choice for those looking to migrate from Firebase while staying within the Google Cloud ecosystem.
We have no reviews of DevGhost.pro yet. Be the first one to post
Recommendations tracked on public social media and blogs since March 2021.


If this sounds like Cloud Functions, here's the history. Cloud Functions 1st gen ran on older, separate infrastructure with strict limits: 9-minute timeouts, one request per instance, no concurrency. Cloud Functions 2nd gen (GA in 2022)... - Source: dev.to / 8 months ago
Cloud Functions (GCF) -- originally serverless functions to compete with AWS Lambda; latest generation rebranded as Cloud Run Functions. - Source: dev.to / 11 months ago
Of course, I can't just directly give my static website permissions to modify my databases, which is why I created a Cloud Function as a "middle-man" -- we should always assume there will be malicious actors that will cause irreparable... - Source: dev.to / about 1 year ago
Tracking DevGhost.pro since Oct 2026.
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