Best Development Frameworks for Microsoft Azure

Compare the Top Development Frameworks that integrate with Microsoft Azure as of July 2025

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This a list of Development Frameworks that integrate with Microsoft Azure. Use the filters on the left to add additional filters for products that have integrations with Microsoft Azure. View the products that work with Microsoft Azure in the table below.

What are Development Frameworks for Microsoft Azure?

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 Microsoft Azure currently available using the table below. This list is updated regularly.

1

Vaadin

Vaadin

Vaadin is a web app development platform for Java. It helps you build reliable web apps with great UX faster than before. Building an enterprise web app involves a lot of moving pieces. Vaadin simplifies the process with an integrated web app development platform for Java backends. Vaadin comes with all the components, frameworks, and tools you need to build a reliable, secure, app with great UX. Research shows that good user experience (UX) increases employee engagement, helps digital transformations to succeed, and avoids costly mistakes. The Vaadin Design System provides UI components and UX patterns that help you build consistently good user experiences in every app. Better yet, you can use it to build a custom design system for your organization. Vaadin comes with 45+ UI components that help you build consistent UIs fast. The theme can be customized to match your brand. Vaadin components work with screen readers and assistive devices.

Starting Price: $139 per month

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2

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

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3

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.

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4

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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5

Everyware Software Framework (ESF)

ESF Eurotech

Everyware Software Framework (ESF) is an enterprise-ready IoT framework distributed and supported by Eurotech. Based on Eclipse Kura, the open source Java/OSGi middleware for IoT gateways, ESF adds provisioning, advanced security, remote access, and diagnostics monitoring. It supports ready-to-use field protocols (including Modbus, OPC-UA, S7, FANUC, J1939, J1979, BACnet, IEC 60870-5-101, IEC 60870-5-104, DNP3, M-bus), MQTT connectivity, and a web-based visual data flow programming to acquire data from the field, process it at the edge, and publish it to IoT cloud platforms. ESF features full remote device management through its integration with Everyware Cloud, Eurotech’s IoT integration platform. Develop and manage IoT edge computing applications. Easily connect to IoT devices and cloud services using IoT industrial protocols. Visually compose data flows to manage, analyze, and route data.

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