Best Development Frameworks of 2024

AdonisJS contains everything you need to build a fully functional web application or an API server. Stop wasting time downloading and assembling hundreds upon hundreds of packages. AdonisJS will make you more productive right away. AdonisJS does not have a minimalist approach. We include many core features in the framework to give your projects an advantage. AdonisJS features a rich routing layer that supports route groups, subdomain-based routing and resource resources. AdonisJS controllers are first-class citizens. They can help you move the inline route handlers from dedicated controller files. The framework core also includes support for file uploads. AdonisJS' schema-based validator provides both runtime validations as well as static type safety. Use the AdonisJS template engine to create traditional-style web apps that are server-rendered.

TypeScript and Node.js frameworks for building microservices and APIs that are extensible. LoopBack core that is TypeScript/ES2017 compliant to provide great extensibility. You can easily create powerful APIs with this new creative experience. A new programming model with dependency injection, new concepts like components, mixins and repositories. This version is the most extensible yet. LoopBack 4 CLI can be used to create a project or extend it. The CLI is the fastest way to start a LoopBack 4 project. It follows best practices. LoopBack is an extensible, open-source Node.js framework. It allows you to create dynamic REST APIs without any coding. Access data from the major relational databases MongoDB, SOAP and REST APIs. Integrate model relationships and access control for complex APIs.

Quarkus will tailor your application for GraalVM or HotSpot. Amazingly fast boot time and extremely low RSS memory (not just heap sizes!) It allows for near-instant scale-up and high-density memory usage in container orchestration platforms such as Kubernetes. We use a technique we call compile time boot. Quarkus is a full-stack framework that is cohesive, fun to use, and makes use of a growing number of best-of-breed library libraries. Unified configuration and native executable generation are the key to optimizing developer joy. Zero configurations, live reload within a blink of an eye, and simplified code for the 80% most common uses, while remaining flexible for the 20% remainder. Combining Quarkus with Kubernetes creates an ideal environment to create lightweight, scalable applications. Quarkus significantly improves developer productivity through tooling, prebuilt integrations, and application services.

Your application startup time is not limited by the size of your codebase. This results in a massive leap in startup times, lightning fast throughput, and minimal memory footprint. The framework caches reflection data and loads it for each bean in an application context when you build applications using reflection-based IoC frameworks. Cloud support is included, including cloud runtimes, distributed tracing, discovery services, and distributed tracing. You can quickly configure your favorite data-access layer, and use the APIs to create your own. You can quickly reap the benefits of familiar annotations. You can quickly spin up servers or clients in your unit testing and run them instantly. This API provides a simple, compile time, aspect-oriented programming API, which does not use reflection.

A server that is efficient means a lower cost infrastructure, better responsiveness under load, and happier users. How can you efficiently manage your server's resources, while still ensuring that you are serving as many requests as possible without sacrificing security validations or handy development? Fastify is the answer. Fastify is a web framework that focuses on providing the best developer experience possible. It's inspired by Express and Hapi. It is the fastest web framework in town, according to our knowledge.

Modular architecture allows for true flexibility and allows you to use any other libraries. A flexible ecosystem that can be used as a backbone for all types of server-side applications. Uses the latest JavaScript features to bring design patterns and mature solutions into Node.js. A complete development kit for building scalable server-side apps. JavaScript has been the "lingua franca of the web" for both front-end and backend applications in recent years thanks to Node.js. This has led to amazing projects such as Angular, React, and Vue that improve developer productivity and allow the creation of fast, extensible, and testable frontend applications. There are many great libraries, tools, and helpers for Node (and JavaScript server-side), but none of them solve the main problem of Architecture.

We believe that the most effective and differentiated applications won't only call out via an API to a language model. LangChain supports several modules. We provide examples, how-to guides and reference docs for each module. Memory is the concept that a chain/agent calls can persist in its state. LangChain provides a standard interface to memory, a collection memory implementations and examples of agents/chains that use it. This module outlines best practices for combining language models with your own text data. Language models can often be more powerful than they are alone.

FastAPI is an advanced web framework that allows you to build APIs using Python 3.7+. It uses standard Python type hints. Fast: Very high-performance, on par with NodeJS or Go (thanks Pydantic and Starlette). One of the fastest Python Frameworks available. Reduce code duplication and get multiple features out of each parameter declaration.

Core ML creates a model by applying a machine-learning algorithm to a collection of training data. A model is used to make predictions using new input data. Models can perform a variety of tasks which would be difficult to code or impractical. You can train a model, for example, to categorize images or detect specific objects in a photo based on its pixels. After creating the model, you can integrate it into your app and deploy on the device of the user. Your app uses Core ML and user data to make forecasts and train or fine-tune a model. Create ML, which is bundled with Xcode, allows you to build and train a ML model. Create ML models are Core ML formatted and ready to be used in your app. Core ML Tools can be used to convert models from other machine learning libraries into Core ML format. Core ML can be used to retrain a model on the device of a user.

Starlette comes with an application class called Starlette, which ties all its other functionality together. A list of middleware that will be run for each request. A starlette application always includes two middleware classes. ServerErrorMiddleware is added as the very outermost middleware, to handle any uncaught errors occurring anywhere in the entire stack. ExceptionMiddleware will be added as the innermost middleware to handle any handled exceptions that occur in the routing or the endpoints. Callables for startup handlers may not take arguments and can be either standard or async. Shutdown handler calls do not accept arguments and can be either standard functions, or async function.

Supports both the client and server side HTTP protocol. Both client and server web sockets are supported out-of-the box.

Asyncio provides a foundation for many Python asynchronous frameworks. These include high-performance web and network servers, database connection libraries, task queues distributed across multiple computers, etc. Asyncio can be a great fit for IO bound and high-level network code.

Falcon is a minimalist Python web API Framework for building robust microservices and app backends. The framework is compatible with both ASGI and gevent/meinheld. The Falcon web framework promotes REST architecture. Resource classes implement HTTP handlers to resolve requests and perform transitions. Falcon is a complement to more general Python webframeworks by adding extra reliability, flexibility and performance where you need it. You can use a number of Falcon templates, add-ons and complementary packages in your projects. You can find a few of these on the Falcon Wiki as a start, but you might also want to search PyPI for more resources.

As always, the first step is to model your data. Applications come and go but data will never disappear. Once your model has been implemented, CubicWeb will run and you can add high-value functionality for your users. RQL is compact language based on the application model. It focuses on the attributes and relationships between data. It is similar in syntax to SPARQL, but more readable for humans. After a RQL query has selected a graph, several views are available to display the data in the most relevant manner. This pattern is used to design the entire CubicWeb architecture. Permissions can be defined with unlimited precision in the data model. Any RQL request sent to the engine is automatically accompanied by security checks. CubicWeb relies upon a standard SQL-based database to store and manage data. CubicWeb prefers PostgreSQL as its database.

Sinatra has a number built-in settings which control the activation of certain features. The settings object is a request context object that contains application-level variables. These variables can be modified by using the set, disable, or enable methods. Applications can set their own custom settings, as well as default built-in framework settings. In its simplest form the set method creates an application attribute by taking a setting value and name. Extensions provide helper methods or class methods to Sinatra applications. These methods are usually listed and described in the extension home pages. Installing a gem, library or a file is all that's needed to use an extension.

A Ruby framework that allows you to create REST-like APIs.

Padrino is designed to make it easy and fun to code more complex web applications, while still retaining the spirit of Sinatra. The Padrino codebase has been kept simple, easy to understand and maintain. The generator creates a compact and clean directory structure for each new project, keeping your code well-organized and simple. This framework is easy to use for web development, whether you are working on a small json web application or a large full stack web application. Sinatra is a popular framework because of its simplicity and expressiveness. However, when building complex applications, many people find that they are missing out on a lot of functionality offered by other frameworks like Rails. We have developed a new approach to a web framework based on this assumption.

Spark Framework is an expressive and simple Java/Kotlin DSL for rapid web development. Sparks goal is to provide a better alternative for Kotlin/Java web developers who want to create their web applications with minimal boilerplate and as expressive as possible. Spark has a clear philosophy that aims to not only make you more productive but also make your code better with Spark's declarative, expressive and sleek syntax. The JVM is one of the largest programming ecosystems on the planet. There are many Java web frameworks available, but traditional Java web development is very difficult. Spark is a web framework that you should use if you love the JVM but dislike verbose frameworks and code.

Create asynchronous server and client applications. Simple and easy to use, you can create anything from microservices up to multiplatform HTTP clients. Open Source, fun, and free! Ktor was built from the ground-up using Kotlin. You can use a multiplatform, concise language with asynchronous programming and an intuitive imperative flow. Ktor lets you use only the features you need and structure your application in the way you want. You can also easily extend Ktor by adding your own plugin. JetBrains is the creators of IntelliJ IDEA and Kotlin. JetBrains uses Ktor internally as well as with our customers. You also get top-notch support for your tooling!

TypeORM can run on NodeJS, Browsers, Cordovas, PhoneGaps, Ionics, React Natives, NativeScripts, Expos, and Electron platforms. It can also be used with TypeScript or JavaScript (ES5, ES6, ES7 and ES8). Its goal to always support the most recent JavaScript features, and provide additional features to help you develop any type of application that uses databases. This includes small applications that use a few tables up to large enterprise applications that use multiple databases. TypeORM supports Active Record and Data Mapper Patterns, unlike other JavaScript ORMs. This allows you to write high-quality, loosely coupled applications that are scalable, maintainable, and scalable.

Slim is a great tool for creating APIs that consume data, repurpose it, or publish it. Slim is a great tool to create rapid prototypes. You can even create full-featured web apps with user interfaces. Slim is also super fast and requires very little code. You don't need to use a solution that has everything like Symfony and Laravel. These are excellent tools, no doubt. They are often overkill. Slim offers a minimal set that does exactly what you need. You will need a webserver like Nginx, Apache or similar. Slim apps contain routes that respond to HTTP requests. Each route calls a callback, and returns an HTTP reply. To get started you must first configure and instantiate the Slim application. Next, you define your application routes.

Feathers works with any backend technology and supports many databases right out of the box. It also works with any frontend technologies like React, VueJS or Angular. Build prototypes within minutes and production-ready applications in days. Feathers' unique architecture lets you focus on quickly building real-time apps and APIs. You get scalable HTTP real-time APIs, and you're prepared for the future. Feathers is compatible with NodeJS in the browser, React Native, or any other API client. You can connect your API to any frontend framework and use any database that supports many features out of the box. Feathers is built for TypeScript and provides the structure needed to create complex applications, but it's flexible enough to avoid getting in the way. With a wide range of plugins, you can find exactly what you are looking for.

Creating ML applications should be easy and frictionless. UnionML is a Python framework that is built on Flyte™ and unifies the ecosystem of ML software into a single interface. Combine the tools you love with a simple, standard API. This allows you to stop writing boilerplate code and focus on the important things: the data and models that learn from it. Fit the rich ecosystems of tools and frameworks to a common protocol for Machine Learning. Implement endpoints using industry-standard machine-learning methods for fetching data and training models. Serve predictions (and more) in order to create a complete ML stack. UnionML apps can be used by data scientists, ML engineers, and MLOps professionals to define a single source for truth about the behavior of your ML system.

Remix is an integrated server and browser runtime. It provides instant page transitions and quick page loads by leveraging distributed systems, native browser features and avoiding clunky static build. It can run anywhere because it is built on the Web Fetch API, instead of Node. Cloudflare Workers already runs it natively, and supports both serverless and traditional Node.js environment, so you can come just as you are. Page speed is just one aspect of what we're really after. We're after better user experiences. Your tools haven't kept up with your desire to push the boundaries of the internet. Remix is here to help you with your initial request and the most elaborate UX that your designers can come up with. Make some pending UI with transition hooks. Remix takes care of all the state. You just need to ask for it.

Apache Mahout is an incredibly powerful, scalable and versatile machine-learning library that was designed for distributed data processing. It provides a set of algorithms that can be used for a variety of tasks, such as classification, clustering and recommendation. Mahout is built on top of Apache Hadoop and uses MapReduce and Spark for data processing. Apache Mahout(TM), a distributed linear-algebra framework, is a mathematically expressive Scala DSL that allows mathematicians to quickly implement their algorithms. Apache Spark is recommended as the default distributed back-end, but can be extended to work with other distributed backends. Matrix computations play a key role in many scientific and engineering applications such as machine learning, data analysis, and computer vision. Apache Mahout is designed for large-scale data processing, leveraging Hadoop and Spark.