What tech stack does Rippling use?
Rippling's engineering stack centers on Python and Django on the backend, React on the web and React Native on mobile, with MongoDB as a core datastore, all running on AWS. The detail below is detected from public sources — Rippling's AWS case study, its engineering blog, StackShare, and job postings — so it reflects what Rippling builds with rather than a vendor list it has confirmed.
- Backend
- Python (Django)
- Web
- React
- Mobile
- React Native
- Data
- MongoDB
- Cloud
- AWS
- Mobile CI
- Bitrise
Detected technologies
What Rippling builds with, grouped by layer (from its AWS case study, StackShare, and job posts).
- Python· Backend
- Django· Backend
- React· Frontend
- React Native· Mobile
- MongoDB· Data
- AWS· Infrastructure
- Bitrise· DevOps
Sources:AWS — Rippling case study
What does Rippling use on the backend and data layer?
Rippling's backend is built primarily in Python with the Django framework, backed by MongoDB as a core datastore — a document model that suits its flexible, ever-expanding 'Employee Graph' of people, devices, apps, and policies. It runs on AWS, and has publicly described migrating more than 100 NoSQL database clusters to AWS database services with near-zero downtime as it consolidated and scaled its data architecture.
What does Rippling use on the frontend and mobile?
On the web, Rippling builds with React, and its mobile apps use React Native to share code across iOS and Android. The company has written about its mobile CI/CD journey — experimenting with GitHub Actions before moving to Bitrise to build and release its iOS and Android apps at scale — reflecting the engineering investment required to ship a product surface spanning two dozen modules.
What Rippling's stack means if you sell to them
Rippling's heavy Python, AWS, and MongoDB footprint maps cleanly to infrastructure, data, observability, and developer-tooling pitches, and its public AWS migration work signals a team comfortable re-platforming when it improves scale. Because it builds a broad product suite in-house, integration and augmentation tend to land better than wholesale replacement. Treat detected stack data as directional and confirm specifics during discovery.
As of June 2026.Sources:AWS — Rippling case studyRippling Blog — mobile CI/CD with Bitrise
Rippling — frequently asked questions
