Programming Languages Used by FAANG in 2026
Which languages actually run the biggest tech companies? Not what they talk about — what they ship. FAANG and its successors (Meta, Apple, Amazon, Netflix, Google, plus Microsoft) collectively employ hundreds of thousands of engineers. Their language choices shape hiring markets, framework ecosystems, and what the next generation of developers learns.
Google is unusual among the FAANG group in that it created two major languages now used industry-wide: Go and Dart. Its internal codebase spans an enormous range — from search-ranking pipelines in C++ to YouTube recommendations in Python to Android apps in Kotlin.
Python— ML, internal tooling, YouTube
Python is the dominant language for machine learning research and production at Google. TensorFlow was developed internally at Google Brain before open-sourcing. YouTube uses Python extensively for its recommendation pipeline and internal tooling.
Go— Internal services, cloud infrastructure
Go was designed by Google engineers (Rob Pike, Ken Thompson, Robert Griesemer) and open-sourced in 2009. Kubernetes — the dominant container orchestration system — was written in Go at Google. Google Cloud Platform uses Go heavily in its backend services.
C++— Chrome, Android runtime, performance-critical infrastructure
Chrome's rendering engine (Blink), the V8 JavaScript engine, and Android's ART runtime are all C++. Google Search's core ranking and retrieval systems run on C++. When performance is the constraint, C++ is Google's default.
Java / Kotlin— Android
Android was originally built as a Java platform. Google shifted its official Android development recommendation to Kotlin in 2017 — Kotlin is now the primary language for new Android development, both internally and in the Android SDK APIs.
JavaScript / TypeScript— Web frontend
Google Maps, Google Docs, Gmail, and Google Search's UI are all built on JavaScript. Google developed Angular (formerly AngularJS), which remains a dominant choice for large enterprise web applications.
Dart— Flutter
Dart is another Google-created language — built specifically as the language for Flutter, Google's cross-platform UI framework. Flutter lets teams ship to iOS, Android, web, and desktop from a single Dart codebase. Dart is not widely used outside the Flutter ecosystem.
Meta (Facebook)
Meta's language story is defined by a willingness to create or heavily modify languages when existing tools fall short. PHP, React, Hack, and PyTorch all originated at Meta. Its production stack mixes a legacy PHP/Hack foundation with modern Python AI infrastructure and React on the frontend.
PHP / Hack— facebook.com backend
Facebook was built on PHP and the company never fully rewrote it. Instead, Meta created Hack — a statically typed superset of PHP that adds type annotations, async/await, and stricter null safety. The Hack Virtual Machine (HHVM) runs facebook.com. This is the most common answer that surprises engineers learning about Meta's stack.
Python— ML/AI — PyTorch is Meta's framework
PyTorch was developed at Meta AI Research (FAIR) and open-sourced in 2016. It is now one of the two dominant deep learning frameworks globally (alongside Google's TensorFlow/JAX). Meta's AI research — including the LLaMA model family — runs on PyTorch in Python.
C++— Mobile performance, Messenger, WhatsApp native layers
WhatsApp's server was originally Erlang, but Meta has progressively rewritten performance-critical components in C++. Messenger's native mobile layers use C++ for cross-platform core logic. Mobile apps at Meta scale require C++ for the performance-critical paths.
JavaScript / React— All web frontends
React was created by Jordan Walke at Facebook and open-sourced in 2013. It is now the most widely adopted UI library in the world. Meta uses React across facebook.com, Instagram web, and its internal tooling. React Native extends this to mobile.
Rust— Buck2 build system, HHVM components
Meta rewrote its build system (Buck) in Rust — the result, Buck2, was open-sourced in 2023. Rust is also used in components of the HHVM runtime and select infrastructure services where memory safety and performance are both required.
Amazon / AWS
Amazon built its service-oriented architecture earlier than any FAANG peer — the internal mandate to expose everything as a service via APIs predates the public cloud era. That heritage means Amazon's internal stack is dominated by Java, the enterprise-grade choice of the early 2000s. AWS itself has embraced Go and Rust for newer infrastructure-level work.
Java— The majority of internal services and AWS backend
Java is the dominant language at Amazon by volume. The core Amazon retail platform, order management, fulfilment, and the majority of AWS service backends are Java. Amazon developed its own JVM optimisations and Java tooling at scale that is not publicly available.
Python— Lambda default, ML, data science
AWS Lambda lists Python as its most-used runtime. Amazon's ML platform (SageMaker) and internal data science tooling run primarily on Python. Alexa's NLP research stack is Python-based.
JavaScript / TypeScript— Frontend, CDK infrastructure-as-code
The AWS CDK (Cloud Development Kit) — the dominant modern way to define AWS infrastructure programmatically — is written in TypeScript and offers TypeScript as its primary interface. AWS Amplify and the AWS Console frontend use JavaScript/TypeScript.
C++— Performance-critical services
Amazon's Dynamo-family databases, performance-critical parts of the S3 storage system, and low-level EC2 virtualisation components use C++. Where latency is measured in microseconds, C++ is the choice.
Go— AWS tooling, growing in services
Go adoption at AWS has grown steadily since the mid-2010s. The AWS CLI v2 is written in Python, but many newer internal AWS tools and service components are written in Go. It is positioned as the modern alternative to Java for new service development.
Rust— Firecracker VMM, Bottlerocket OS
Two of Amazon's most significant open-source infrastructure contributions are written in Rust: Firecracker (the microVM hypervisor that powers AWS Lambda and Fargate) and Bottlerocket (the container-optimised Linux OS). Both require the memory safety guarantees that Rust provides.
Apple
Apple's language story is one of the most decisive transitions in the industry. The company spent decades on Objective-C, created Swift in 2014 to replace it, and has followed through: Swift is now the primary language for every first-party Apple app. The underlying OS still relies on C and C++.
Swift— iOS, macOS, all first-party apps
Apple created Swift in 2014 and open-sourced it in 2015. It is now the primary language for iOS and macOS application development — both internally (Xcode, Safari, Maps, Photos) and for the developer ecosystem. Swift Concurrency (async/await, actors) was added in Swift 5.5, addressing a longstanding pain point.
Objective-C— Legacy, declining
Objective-C was the primary iOS and macOS development language from the iPhone's introduction in 2007 until Swift. Large amounts of Apple's own frameworks still expose Objective-C APIs, and many older apps remain in Objective-C. New development at Apple is Swift.
C / C++— OS kernel, low-level frameworks
The XNU kernel (macOS, iOS, watchOS, tvOS) is written in C and C++. Core system frameworks like Core Foundation are C. Apple's graphics stack (Metal shaders) uses a C-derivative language. At the OS layer, C and C++ remain irreplaceable.
Python— ML research, internal tooling
Apple's Core ML team and AI research groups use Python. Apple Silicon's ML accelerator (the Neural Engine) is optimised partly via Python-based tooling. Python is the research layer; Swift is the deployment layer for on-device ML via Core ML.
JavaScript— WebKit
WebKit — the browser engine powering Safari and all browsers on iOS — has a substantial JavaScript codebase (the JavaScriptCore engine). Web content on Apple platforms runs through WebKit's JavaScript implementation.
Netflix
Netflix has contributed more to the Java microservices ecosystem than any other single company. Hystrix (circuit breaker), Eureka (service registry), Ribbon (client load balancing), and Zuul (API gateway) — the foundational building blocks of Java microservice architecture — all came from Netflix OSS. The backend is Java; the recommendation intelligence is Python.
Java— Backend microservices — the dominant language
Netflix's streaming backend — content delivery routing, account management, billing, device compatibility — runs on a large Java microservices architecture hosted on AWS. The Netflix OSS libraries (Hystrix, Eureka, Ribbon, Zuul) that defined the Java microservices pattern came from Netflix's internal infrastructure.
Python— ML recommendation engine, data science
Netflix's recommendation engine — the system that determines what each user sees on their home screen — is powered by Python-based ML. The Netflix data science team is one of the largest in the industry. Python is the language of choice for all ML and data analysis work.
JavaScript / Node.js— API gateway layer
Netflix uses Node.js as the API orchestration layer that aggregates data from backend microservices and serves it to client applications. This pattern (Node.js as a BFF — Backend for Frontend) is well-documented in Netflix engineering blog posts.
Kotlin— Android, growing in backend
The Netflix Android app is being migrated to Kotlin. Kotlin is also seeing growing use in Netflix's backend services as a modern alternative to Java on the JVM — it offers interoperability with existing Java code while adding null safety and more concise syntax.
Go— Tooling and infrastructure
Go is used for internal tooling, build systems, and infrastructure automation at Netflix. It is not a primary application language but appears wherever teams need fast, self-contained binaries for operational tooling.
Microsoft
Microsoft's language portfolio is as wide as any in the industry — it has to be, because the company makes Windows, Azure, GitHub, VS Code, Office, Xbox, and Teams. Notably, Microsoft created TypeScript and has invested heavily in Rust for systems-level security work.
C#— Windows, .NET, Azure
C# is Microsoft's flagship language and the foundation of the .NET platform. Windows system components, Azure's control plane services, Xbox platform services, and large portions of Microsoft 365 (Exchange, SharePoint) are written in C#. The .NET runtime itself is a massive open-source C# codebase.
TypeScript— VS Code, Azure portal, Teams — Microsoft created it
TypeScript was created by Anders Hejlsberg at Microsoft and open-sourced in 2012. VS Code — the most widely used code editor globally — is written in TypeScript. The Azure portal frontend and Microsoft Teams web client are TypeScript applications. Microsoft is TypeScript's single largest contributor.
C / C++— Windows kernel, Office, Edge
The Windows NT kernel is C and C++. Office (Word, Excel, PowerPoint) native applications are C++. The Edge browser is built on Chromium (C++). Microsoft maintains some of the largest and oldest C/C++ codebases in the industry.
Python— ML, GitHub Copilot training, data science
Microsoft's AI research — including GitHub Copilot's model training pipeline and Azure AI services — uses Python. After acquiring GitHub, Microsoft has invested in Python tooling (the Pylance language server, Python extensions for VS Code) and uses Python extensively in its ML infrastructure.
Rust— Systems work, security-critical components
Microsoft has formally endorsed Rust for new Windows systems programming. The company joined the Rust Foundation and has engineers working on the Rust compiler. Parts of the Windows kernel and Azure hypervisor components are being written in Rust as a memory-safe alternative to C++.
JavaScript— GitHub, Teams, web properties
GitHub.com is a Ruby on Rails + React application. Microsoft Teams' web client and many Azure portal components are JavaScript/TypeScript. Microsoft runs some of the highest-traffic JavaScript applications in the world.
Cross-FAANG patterns: which languages appear at 4+ companies
Looking across all six companies, clear consensus languages emerge. These are the languages that define the FAANG hiring market — not because one company chose them, but because the industry collectively converged on them.
| Language | Companies | Primary use at FAANG | Trend |
|---|---|---|---|
| Python | 6 / 6 | ML/AI, data science, tooling | Growing |
| JavaScript / TypeScript | 6 / 6 | Web frontend, API layer, tooling | Stable |
| C++ | 5 / 6 | Performance-critical systems, browsers, OS | Stable |
| Java | 4 / 6 | Backend services, Android | Declining slowly |
| Go | 4 / 6 | Infrastructure, cloud tooling, microservices | Growing |
| Rust | 3 / 6 | Systems programming, hypervisors, build tools | Growing fast |
Rust appears at Amazon (Firecracker, Bottlerocket), Meta (Buck2), and Microsoft (Windows systems work). At 3 companies and growing, it is the most significant language movement in the FAANG stack over the past three years.
What this means for your career
FAANG language choices directly shape the hiring market. The languages these companies use at scale are the languages they interview for, hire for, and pay premiums for. Here is how to read the data for your own situation.
The FAANG generalist stack
If your goal is to be hireable across the widest range of FAANG-tier companies and roles, the combination is: Python + one systems language + JavaScript/TypeScript. Python covers ML, data, scripting, and backend. JavaScript/TypeScript covers everything browser-facing and much of the API layer. The systems language — Go, C++, or Rust — covers the infrastructure and performance-critical work that differentiates senior candidates.
Specialist paths
iOS / macOS engineering
Swift (primary) + Objective-C (legacy)
Apple is the only FAANG company where Swift is central. If your target is Apple or the iOS app ecosystem, Swift is non-negotiable. You will encounter Objective-C in older codebases; you do not need to write new Objective-C, but you need to read it.
Android engineering
Kotlin (primary) + Java (legacy)
Google and Meta both have large Android teams. Kotlin has been Google's recommended Android language since 2017. Java is still everywhere in older Android codebases and in the Android SDK internals, but new Android development is Kotlin.
Systems / infrastructure engineering
C++ (established) / Rust (growing)
The FAANG companies with the deepest systems engineering — Google (Chrome, V8, Android runtime), Amazon (Firecracker, Bottlerocket), Microsoft (Windows kernel) — use C++ and increasingly Rust. Systems roles are the highest-paid individual contributor tracks in the industry.
Cloud / DevOps / platform engineering
Go (primary)
Kubernetes, Docker, Terraform, and a large portion of the cloud-native tooling ecosystem are written in Go. If your target is platform engineering at a FAANG-tier cloud company, Go is the language most likely to be relevant to your day-to-day work.
ML / AI engineering
Python (required)
All six companies use Python for ML research and production. PyTorch (Meta) and TensorFlow/JAX (Google) are both Python frameworks. There is no alternative for ML engineering at FAANG companies — Python is the universal requirement.
Full-stack web engineering
JavaScript / TypeScript (required)
Every company in this list runs significant JavaScript/TypeScript. React (Meta-originated), Angular (Google-originated), and TypeScript (Microsoft-originated) are all FAANG-backed. Full-stack TypeScript roles are in demand at all six companies.
The Rust signal: Three FAANG-tier companies (Amazon, Meta, Microsoft) have committed production Rust codebases — not experiments, but production systems handling real load. If you are a C++ engineer evaluating whether to invest in Rust, this is the clearest possible signal: the industry is moving, and the move is happening at the top.
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