AmazonWhat tech stack does Amazon use?
Amazon, unsurprisingly, builds on its own cloud — Amazon Web Services — and a polyglot mix of Java, Python, C++, JavaScript/TypeScript, and Rust, with service-oriented microservices everywhere. The technologies below are detected from public sources (the Amazon/AWS engineering blogs, conference talks, StackShare/BuiltWith-style signals, and job postings), so the list is directional rather than an internal inventory.
- Cloud
- Amazon Web Services (AWS)
- Backend
- Java, C++, Python, Rust, Go
- Frontend
- JavaScript/TypeScript, React
- Data
- DynamoDB, Aurora, Redshift, S3
- Compute
- EC2, Lambda, microservices/SOA
- Silicon
- Graviton, Trainium, Inferentia, Nitro
Amazon's detected tech stack
Polyglot services on AWS — Java/C++/Python/Rust backend, React frontend, AWS-native data, AI, and in-house silicon.
- React· Frontend
- JavaScript / TypeScript· Frontend
- Java· Backend
- C++· Backend
- Python· Backend
- Rust· Backend
- Go· Backend
- Amazon EC2· Infrastructure
- AWS Lambda· Infrastructure
- Amazon S3· Infrastructure
- DynamoDB· Data
- Amazon Aurora / RDS· Data
- Amazon Redshift· Data
- SageMaker & Bedrock· Data / AI
- Graviton / Trainium / Nitro· Silicon
- Swift (iOS) / Kotlin (Android)· Mobile
Sources:AWS architecture & engineering blogAmazon Web Services — Wikipedia
What does Amazon use on the backend and infrastructure?
Amazon's backend is heavily Java and C++ for high-scale services, with Python and increasingly Rust and Go used across systems and performance-sensitive components. Everything runs as service-oriented microservices — the architecture Werner Vogels popularized — deployed on AWS itself.
The infrastructure layer is pure AWS: EC2 and AWS Lambda for compute, S3 for storage, and a deep bench of internal AWS services for queuing, messaging, and orchestration. Increasingly it runs on Amazon's own silicon — Graviton (general compute), Trainium/Inferentia (AI), and Nitro — a chips business now at a $20B+ annual run rate. Amazon is effectively AWS's largest and most demanding customer.
What does Amazon use on the frontend, data, and AI?
On the frontend, Amazon's web properties use JavaScript/TypeScript with React across many surfaces, while its mobile apps are built natively in Swift (iOS) and Kotlin/Java (Android). The retail site itself is a patchwork of independently owned, service-backed pages rather than a single monolith.
For data, Amazon leans on its own managed services — DynamoDB for high-scale key-value workloads, Aurora and RDS for relational data, Redshift for analytics/warehousing, and S3 as the data lake — alongside internal big-data and ML platforms like SageMaker and Bedrock for AI. In 2026 Bedrock added third-party frontier models (including OpenAI models), signaling a more open AI platform layer.
What Amazon's stack means if you sell to them
Amazon is the canonical build-vs-buy 'build' company — it runs on AWS and tends to build internal tooling rather than license third-party platforms, so displacement pitches face a steep wall. The most credible plays are technologies that complement (not replace) AWS-native infrastructure, or that operate at a scale and cost point Amazon can't easily justify building.
Where external vendors do land, it's usually in areas tangential to core infrastructure — security/compliance, developer productivity, or specialized data tooling — and only after clearing a rigorous cost and scale bar. Lead with AWS-native integration and hard ROI, expect deep technical scrutiny from engineering buyers, and align to the current AI-efficiency mandate driving budget.
As of June 2026.Sources:AWS products & servicesAWS architecture blog
Amazon — frequently asked questions
