Best Development Frameworks for Amazon Web Services (AWS)
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Compare the Top Development Frameworks that integrate with Amazon Web Services (AWS) as of November 2025
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This a list of Development Frameworks that integrate with Amazon Web Services (AWS). Use the filters on the left to add additional filters for products that have integrations with Amazon Web Services (AWS). View the products that work with Amazon Web Services (AWS) in the table below.
What are Development Frameworks for Amazon Web Services (AWS)?
Development frameworks are code libraries and development tools that streamline the development process for developers that build applications. Development frameworks simplify the process of programming in different languages. There are a variety of different types of development frameworks including web development frameworks, mobile app development frameworks, frontend and backend frameworks, and more. Compare and read user reviews of the best Development Frameworks for Amazon Web Services (AWS) currently available using the table below. This list is updated regularly.
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1
Gatsby
Gatsby
Gatsby is an open-source, modern website framework that builds performance into every site by leveraging the latest web technologies such as React and GraphQL. Create blazing-fast apps and websites without needing to become a performance expert. Preview is like a private playground for developers, designers, and content creators. It provides a shareable temporary URL for viewing changes immediately and in context—so you can make sure that new header plays nicely with the rest of the page before hitting “publish.” Gatsby Builds is the fastest continuous deployment solution for Gatsby sites and apps—up to 20x faster standard builds times than other solutions, and now up to 1000x faster with Incremental Builds (beta). Use automated Lighthouse performance checks and deploy previews to fix errors before they’re published. Build with Gatsby and deploy to your favorite CDN.Starting Price: $99 per month -
2
Atri Framework
Atri Labs
Atri framework is a full-stack web development framework to build Progressive Web Apps. Use our visual editor to increase your productivity. You can also add your custom React code. Currently, we support Python for backend development. We are planning to add support for NodeJS soon. Our CLI provides rich support for easy deployment at your platform of choice such as GitHub Pages, AWS, etc. Atri framework comes with a suite of productivity tools such as a visual editor, asset management tools, etc. that significantly reduce development time from months to hours. Atri framework is extending the definition of full-stack to include non-web developers in the development and maintenance of an app.Starting Price: $100 per user per month -
3
Nitric
Nitric
Nitric is an open source, cloud-agnostic backend framework that enables developers to declare infrastructure as code and automate deployments using pluggable plugins. It supports multiple languages, including JavaScript, TypeScript, Python, Go, and Dart. Key features include defining APIs (REST, HTTP), serverless functions, routing, authentication/authorization (OIDC-compatible), storage (object/file storage, signed URLs, bucket events), databases (e.g., managed Postgres with migrations), messaging (queues, topics, pub/sub), websockets, scheduled tasks, and secrets management. Nitric integrates with tools like Terraform or Pulumi, or lets you write your own plugins, and works with major cloud providers (AWS, Azure, Google Cloud). It also supports local development with simulated cloud environments so you can prototype, test, and iterate without incurring cloud cost. The framework emphasizes declarative security, resource access management, and portability.Starting Price: Free -
4
Horovod
Horovod
Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data processing and model training into a single pipeline. Once Horovod has been configured, the same infrastructure can be used to train models with any framework, making it easy to switch between TensorFlow, PyTorch, MXNet, and future frameworks as machine learning tech stacks continue to evolve.Starting Price: Free -
5
Statiq
Statiq
A batteries-included static site generator that's appropriate for most use cases. Use it out-of-the-box or extend it with custom pipelines, data sources, and layouts. Extends Statiq Web by adding support for generating .NET API documentation while still benefiting from all the capabilities of a robust general-purpose static site generator. The framework behind Statiq Web and Statiq Docs with over 100 modules to help you easily build a custom static generator application specifically for your needs. Different types of content require different types of templates, and Statiq has you covered with support for Markdown and Razor (along with plain HTML) with more languages like Handlebars/Mustache and Liquid coming soon. Statiq understands a variety of data formats like YAML, JSON, and XML and is designed to plug any data format into any usage. From data files to front matter use the data format you're most comfortable in. -
6
Micronaut
Micronaut Framework
Your application startup time and memory consumption aren’t bound to the size of your codebase, resulting in a monumental leap in startup time, blazing fast throughput, and a minimal memory footprint. When building applications with reflection-based IoC frameworks, the framework loads and caches reflection data for every bean in the application context. Built-in cloud support including discovery services, distributed tracing, and cloud runtimes. Quick configuration of your favorite data-access layer and the APIs to write your own. Realize benefits quickly by using familiar annotations in the way you are used to. Easily spin up servers and clients in your unit tests and run them instantaneously. Provides a simple, compile-time, aspect-oriented programming API that does not use reflection. -
7
UnionML
Union
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior.
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