Open Source Scala Software Development Software for Windows
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Scala Software Development Software for Windows
View 2024 business solutionsBrowse free open source Scala Software Development Software for Windows and projects below. Use the toggles on the left to filter open source Scala Software Development Software for Windows by OS, license, language, programming language, and project status.
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lichess.org
The forever free, ad-free and open source chess server
lichess.org (also known as Lila - lichess in Scala) is a free and open source chess server written in Scala 2.13 that focuses on real time gameplay and ease of use. It’s where countless chess players and chess enthusiasts can gather and watch or play from a selection of over a million games every day, analyze games, learn and improve their playing. lichess is equipped with a search engine, computer analysis, tournaments, exhibitions, a mobile app, a shared analysis board, and so much more. Thanks to its large active community, the UI is available in more than 130 different languages. lichess is one of the most popular chess websites in the world and remains totally free and ad-free. Visit https://lichess.org today to know more and see what it’s about! -
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Coursier
Pure Scala Artifact Fetching
Coursier is the Scala application and artifact manager. It can install Scala applications and setup your Scala development environment. It can also download and cache artifacts from the web. -
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Gatling
Modern Load Testing as Code
Gatling is a high-performance load testing tool built on the JVM that emphasizes realism, scalability, and developer ergonomics. Test scenarios are scripted in a concise Scala-based DSL, allowing you to model user journeys with think times, feeders (dynamic data), checks, and assertions all in code. Its asynchronous, non-blocking engine (backed by Netty) can drive very high concurrency from a single injector, reducing the need for large injector farms. Gatling supports HTTP out of the box as well as WebSocket, Server-Sent Events, and JMS, so you can exercise modern, real-time systems end to end. Rich HTML reports visualize percentiles, response time distributions, errors, and throughput, making bottlenecks and regressions easy to spot. With injection profiles (ramp, constant, spikes) and pass/fail gates, you can automate performance thresholds in CI and promote builds with confidence. -
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scalajs-react
Facebook's React on Scala.JS
Scala.js React wraps Facebook React for Scala.js with a strong emphasis on type safety and functional idioms. It provides a typed virtual DOM interface, reusable components, hooks, and utilities for routing, testing, SSR, and performance profiling, all aligned with Cats, Cats Effect, and Monocle ecosystems. -
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Prisma 1
Database Tools incl. ORM, migrations and admin UI
Prisma is the perfect tool for building GraphQL servers. The Prisma client is compatible with the Apollo ecosystem, has default support for GraphQL subscriptions and Relay-style pagination, provides end-to-end type safety and comes with a built-in dataloader to solve the N+1 problem. Prisma replaces traditional ORMs and simplifies database workflows. Access, Type-safe database access with the auto-generated Prisma client (in JavaScript, TypeScript, Go). Migrate, declarative data modeling and migrations (optional). Manage, visual data management with Prisma Admin. It is used to build GraphQL, REST, gRPC APIs and a lot more. Prisma currently supports MySQL, PostgreSQL, MongoDB. Prisma is a great fit for building REST& gRPC APIs where it can be used in place of traditional ORMs. It provides many benefits such as type safety, a modern API and flexible ways for reading and writing relational data. -
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Caliban
Functional GraphQL library for Scala
Caliban is a purely functional library for building GraphQL servers and clients in Scala. The design principles behind the library are the following. Minimal amount of boilerplate: no need to manually define a schema for every type in your API. Pure interface: errors and effects are returned explicitly (no exceptions thrown), all returned types are referentially transparent (no Future). Clean separation between schema definition and implementation: schema is defined and validated at compile time using Scala standard types, resolver (RootResolver) is a simple value provided at runtime. All interfaces are pure and types are referentially transparent. Schemas are type safe and derived at compile time. No need to manually define a schema for every type in your API. Let the compiler do the boring work. Out-of-the-box support for major HTTP server libraries, effect types, Json libraries and more. -
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Spark JobServer
REST job server for Apache Spark
Spark Job Server offers a RESTful interface for submitting, managing, and running jobs or contexts on Apache Spark. Rather than requiring every application to embed Spark or manage Spark contexts manually, this server abstracts a long-lived service where clients can upload JARs, start and stop contexts, submit jobs synchronously or asynchronously, and manage named objects (RDDs / DataFrames) across job executions. It supports multiple modes (transient jobs, persistent contexts for reuse, streaming, SQL/Hive, etc.), and can be integrated with authentication/authorization systems (e.g. via Apache Shiro). The architecture isolates Spark contexts (optionally in separate JVMs), isolates job dependencies, and persists job / jar metadata via pluggable DAOs. It supports deployment across cluster managers (YARN, Mesos, etc.) and aims to simplify Spark-as-a-service scenarios. -
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FiloDB
Distributed Prometheus time series database
FiloDB is an open-source distributed, real-time, in-memory, massively scalable, multi-schema time series / event / operational database with Prometheus query support and some Spark support as well. The normal configuration for real-time ingestion is deployment as stand-alone processes in a cluster, ingesting directly from Apache Kafka. The processes form a cluster using peer-to-peer Akka Cluster technology. Designed to ingest many millions of entities, sharded across multiple processes, with distributed querying built in. Support for indexing and fast querying over flexible tags for each time series/partition, just like Prometheus. Holds a huge amount of data in-memory thanks to columnar compression techniques. Designed for highly concurrent, low-latency workloads such as dashboards and alerting. Data immediately available for querying once ingested. -
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Kamon Telemetry
Distributed Tracing, Metrics and Context Propagation for applications
Kamon Telemetry is a set of libraries for instrumenting applications running on the JVM. With Kamon Telemetry you can collect metrics, propagate context across threads and services, and get distributed traces automatically. The best way to get started is by following our installation guides and taking it from there. Have fun with Kamon. Monitor your backend applications, fix performance issues, and get alerted when problems happen. All without being a monitoring expert. Everybody starts monitoring with logs because they are there by default. Just connect to your server and start tailing. But logs have a hard time showing you the overall response times for your application, or whether certain calls to the database are happening in sequence or parallel (among a million other things). -
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Sangria
Scala GraphQL implementation
Sangria is a Scala GraphQL implementation. It is an example of GraphQL server written with Play framework and Sangria. It also serves as a playground, where you can interactively execute GraphQL queries and play with some examples. If you want to use sangria with a react-relay framework, then you also may be interested in sangria-relay. Sangria is a spec-compliant GraphQL implementation, so it works out of the box with Apollo, Relay, GraphiQL and other GraphQL tools and libraries. Since GraphQL has a type system, the server defines a schema that the client can query using the introspection API. This provides the client with a set of possibilities. After the client got this information and decided which parts of the data it needs, it is able to describe its data requirements in form of a GraphQL query. An important aspect of GraphQL is that it’s completely backend agnostic. -
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Scala.js
Scala.js, the Scala to JavaScript compiler
Strong typing guarantees your code is free of silly mistakes; no more mixing up strings or numbers, forgetting what keys an object has, or worrying about typos in your method names. Scala.js takes care of all this tedious book-keeping for you, letting you focus on the actual, more interesting problem your application is trying to solve. Scala.js optimizes your Scala code into highly efficient JavaScript. Incremental compilation guarantees speedy (1-2s) turn-around times when your code changes. The generated JavaScript is both fast and small, starting from 45kB gzipped for a full application. Scala.js loves JavaScript libraries, including React and AngularJS. You can use any JavaScript library right from your Scala.js code, either in a statically or dynamically typed way. You won't even notice you're crossing a language border! -
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Slick database
Slick (Scala Language Integrated Connection Kit) is a modern database
Slick is a modern database query and access library for Scala. It allows you to work with stored data almost as if you were using Scala collections while at the same time giving you full control over when a database access happens and which data is transferred. You can write your database queries in Scala instead of SQL, thus profiting from the static checking, compile-time safety and compositionality of Scala. Slick features an extensible query compiler which can generate code for different backends. It allows you to work with relational databases almost as if you were using Scala collections, while at the same time giving you full control over when a database access happens and what data is transferred. By writing your queries in Scala you can benefit from the static type checking, compile-time safety, and compositionality of Scala, while retaining the ability to drop down to raw SQL where needed for custom or advanced database features. -
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Akka
Build concurrent, distributed, and resilient message-driven apps
Build powerful reactive, concurrent, and distributed applications more easily. Akka is a toolkit for building highly concurrent, distributed, and resilient message-driven applications for Java and Scala. Actors and Streams let you build systems that scale up, using the resources of a server more efficiently, and out, using multiple servers. Building on the principles of The Reactive Manifesto Akka allows you to write systems that self-heal and stay responsive in the face of failures. Up to 50 million msg/sec on a single machine. Small memory footprint; ~2.5 million actors per GB of heap. Distributed systems without single points of failure. Load balancing and adaptive routing across nodes. Event Sourcing and CQRS with Cluster Sharding. Distributed Data for eventual consistency using CRDTs. Asynchronous non-blocking stream processing with backpressure. -
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Apache Spark
A unified analytics engine for large-scale data processing
Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing. With Spark Streaming (microbatches) and Structured Streaming, it delivers low-latency event processing suitable for real-time analytics. The built-in MLlib library provides scalable machine learning algorithms, while GraphX enables graph computations integrated with data pipelines. Spark supports multiple languages—Scala, Java, Python, R—and connects with many storage systems like HDFS, S3, Cassandra, and streaming platforms like Kafka, making it a versatile choice for big data workloads in analytics, ETL, and data science. -
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Scala Steward
A bot that helps you keep your projects up-to-date
Scala Steward is an automated tool that helps to keep Scala libraries and plugins up to date by checking for dependency updates and sending pull requests. -
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Skunk
A data access library for Scala + Postgres
Skunk is a Postgres library for Scala. Skunk is powered by cats, cats-effect, scodec, and fs2. Skunk is purely functional, non-blocking, and provides a tagless-final API. Skunk gives very good error messages. Skunk embraces the Scala Code of Conduct. Skunk is pre-release software! Code and documentation are under active development! Skunk is published for Scala 2.12/2.13/3.1 and can be included in your project.Query and Command types are usually inferrable, but specifying a type ensures that the chosen encoders and decoders are consistent with the expected input and output Scala types. Postgres provides a protocol for execution of simple queries, returning all rows at once (Skunk returns them as a list). -
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s3_website
Manage an S3 website: sync, deliver via CloudFront
s3_website is a Ruby gem that automates the deployment of static websites to AWS S3 and optionally CloudFront. It handles site configuration, uploads, cache control, gzip compression, redirects, and supports Jekyll, Nanoc, and Middleman out of the box. Ideal for static site hosting without manual AWS setup. -
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scalafmt
Code formatter for Scala
The Scala plugin compatible with recent versions of IntelliJ IDEA has built-in support for Scalafmt. Spend more time discussing important issues in code review and less time on code style. Scalafmt formats code so that it looks consistent between people on your team. Run scalafmt from your editor, build tool or terminal. Scalafmt has integrations with IntelliJ, sbt, Maven, Gradle and Mill. Choose the scalafmt formatter and IntelliJ's Reformat Code action will then use Scalafmt when formatting files. Scalafmt is primarily designed to operate on entire text files—formatting selected ranges of code may produce undesirable results. For this reason, IntelliJ uses its own formatter for ranges by default. It is not recommended to change this, and is instead recommended to format files when saving. -
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Alpakka Kafka
Alpakka is a Reactive Enterprise Integration library for Java
The Alpakka project is an open source initiative to implement stream-aware and reactive integration pipelines for Java and Scala. It is built on top of Akka Streams and has been designed from the ground up to understand streaming natively and provide a DSL for reactive and stream-oriented programming, with built-in support for backpressure. Akka Streams is a Reactive Stream and JDK 9+ java.util.concurrent.Flow-compliant implementation and therefore fully interoperable with other implementations. As Kafka’s client protocol negotiates the version to use with the Kafka broker, you may use a Kafka client version that is different than the Kafka broker’s version. -
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Cats
Lightweight, modular, extensible library for functional programming
Cats is a library which provides abstractions for functional programming in the Scala programming language. The name is a playful shortening of the word category. Scala supports both object-oriented and functional programming, and this is reflected in the hybrid approach of the standard library. Cats strives to provide functional programming abstractions that are core, binary compatible, modular, approachable and efficient. A broader goal of Cats is to provide a foundation for an ecosystem of pure, typeful libraries to support functional programming in Scala applications. Cats strives to provide a solid and stable foundation for an ecosystem of FP libraries. Thus, we treat backward binary compatibility maintenance with a high priority. In semantic versioning, backward breaking change is only allowed between major versions. -
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Cats Effect
The pure asynchronous runtime for Scala
Cats-Effect is a high-quality functional programming library for Scala that provides a principled way to represent and manage side effects, particularly asynchronous and concurrent computations. It is part of the broader Typelevel ecosystem and builds on the abstractions from Cats (such as Functor, Monad, etc.). The core abstraction is the IO type (or effect types more generally), which encodes effectful computations in a pure, referentially transparent way. Cats-Effect offers capabilities like deferred execution, cancellation, resource safety (Resource), fiber concurrency (lightweight threads), and interoperation with underlying runtime platforms (JVM, Java concurrency, etc.). It enables developers to write effectful code while preserving composability, purity, and modular reasoning about side effects. -
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Dotty
The scala 3 compiler, also known as Dotty
The exciting new version of Scala 3 brings many improvements and new features. Scala 3 is a complete overhaul of the Scala language. At its core, many aspects of the type-system have been changed to be more principled. While this also brings exciting new features along (like union types), first and foremost, it means that the type-system gets (even) less in your way and for instance type-inference and overload resolution are much improved. One underlying core concept of Scala was (and still is to some degree) to provide users with a small set of powerful features that can be combined to great (and sometimes even unforeseen) expressivity. For example, the feature of implicits has been used to model contextual abstraction, to express type-level computation, model type-classes, perform implicit coercions, encode extension methods, and many more. Learning from these use cases, Scala 3 takes a slightly different approach and focuses on intent rather than mechanism. -
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FS2
Compositional, streaming I/O library for Scala
FS2 (“Functional Streams for Scala”) is a purely functional, effectful abstraction for stream processing on the JVM. Built on Cats Effect, it enables compositional resource-safe streaming workflows with robust error handling, back-pressure, pull/push semantics, and support for concurrent and interruptible pipelines. -
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SpinalHDL
Scala based HDL
SpinalHDL is a hardware description (HDL) framework embedded in Scala, enabling hardware designers to build digital circuits with modern programming abstractions. Instead of writing in Verilog or VHDL directly, users describe hardware components and their interconnects using Scala code and Spinal’s domain-specific library, which then emits synthesizable hardware (e.g. as Verilog). Because SpinalHDL is embedded in Scala, it allows reuse of functional abstractions, parameterization, modular composition, and higher-level constructs to manage complexity. It supports building systems at various levels—single modules, pipelines, memories, controllers, etc.—while letting the designer control timing, pipelining, and resource sharing explicitly. The generated hardware can be synthesized for FPGAs or ASIC flows, making it practical for real designs. -
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tapir
Declarative, type-safe web endpoints library
Declarative, type-safe web endpoints library. With tapir, you can describe HTTP API endpoints as immutable Scala values. Each endpoint can contain a number of input and output parameters. Compile-time guarantees, develop-time completions, read-time information. Separate the shape of the endpoint (the "what"), from the server logic (the "how"). Generate documentation from endpoint descriptions. Leverage the metadata to report rich metrics and tracing information. Re-use common endpoint definitions, as well as individual inputs/outputs. Library, not a framework, integrates with your stack. Is your company already using tapir? We're continually expanding the "adopters" section in the documentation; the more the merrier! It would be great to feature your company's logo, but in order to do that, we'll need to write permission to avoid any legal misunderstandings.
