Alternatives to SBT logo

Alternatives to SBT

Gradle, C lang, Apache Maven, Scala, and Bazel are the most popular alternatives and competitors to SBT.
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What is SBT and what are its top alternatives?

It is similar to Java's Maven and Ant. Its main features are: Native support for compiling Scala code and integrating with many Scala test frameworks.
SBT is a tool in the Java Build Tools category of a tech stack.

Top Alternatives to SBT

  • Gradle
    Gradle

    Gradle is a build tool with a focus on build automation and support for multi-language development. If you are building, testing, publishing, and deploying software on any platform, Gradle offers a flexible model that can support the entire development lifecycle from compiling and packaging code to publishing web sites. ...

  • C lang
  • Apache Maven
    Apache Maven

    Maven allows a project to build using its project object model (POM) and a set of plugins that are shared by all projects using Maven, providing a uniform build system. Once you familiarize yourself with how one Maven project builds you automatically know how all Maven projects build saving you immense amounts of time when trying to navigate many projects. ...

  • Scala
    Scala

    Scala is an acronym for “Scalable Language”. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them. ...

  • Bazel
    Bazel

    Bazel is a build tool that builds code quickly and reliably. It is used to build the majority of Google's software, and thus it has been designed to handle build problems present in Google's development environment. ...

  • Mill
    Mill

    It is your shiny new Java/Scala build tool. It aims for simplicity by re-using concepts you are already familiar with, borrowing ideas from modern tools like Bazel, to let you build your projects in a way that's simple, fast, and predictable. ...

  • CMake
    CMake

    It is used to control the software compilation process using simple platform and compiler independent configuration files, and generate native makefiles and workspaces that can be used in the compiler environment of the user's choice. ...

  • Sonatype Nexus
    Sonatype Nexus

    It is an open source repository that supports many artifact formats, including Docker, Java™ and npm. With the Nexus tool integration, pipelines in your toolchain can publish and retrieve versioned apps and their dependencies ...

SBT alternatives & related posts

Gradle logo

Gradle

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A powerful build system for the JVM
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PROS OF GRADLE
  • 110
    Flexibility
  • 51
    Easy to use
  • 47
    Groovy dsl
  • 22
    Slow build time
  • 10
    Crazy memory leaks
  • 8
    Fast incremental builds
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    Kotlin DSL
  • 1
    Windows Support
CONS OF GRADLE
  • 7
    Inactionnable documentation
  • 6
    It is just the mess of Ant++
  • 4
    Hard to decide: ten or more ways to achieve one goal
  • 2
    Bad Eclipse tooling
  • 2
    Dependency on groovy

related Gradle posts

Shared insights
on
Apache MavenApache MavenGradleGradle
at

We use Apache Maven because it is a standard. Gradle is very good alternative, but Gradle doesn't provide any advantage for our project. Gradle is slower (without running daemon), need more resources and a learning curve is quite big. Our project can not use a great flexibility of Gradle. On the other hand, Maven is well-know tool integrated in many IDEs, Dockers and so on.

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Utilities

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DevOps

GitHub Docker Webpack CircleCI Jenkins Travis CI Gradle Apache Maven

Cooperation Tools

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C lang logo

C lang

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One of the most widely used programming languages of all time
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PROS OF C LANG
  • 67
    Performance
  • 48
    Low-level
  • 35
    Portability
  • 28
    Hardware level
  • 19
    Embedded apps
  • 13
    Pure
  • 9
    Performance of assembler
  • 8
    Ubiquity
  • 5
    Great for embedded
  • 4
    Old
  • 3
    Compiles quickly
  • 2
    No garbage collection to slow it down
  • 2
    OpenMP
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    Gnu/linux interoperable
CONS OF C LANG
  • 5
    Low-level
  • 3
    No built in support for concurrency
  • 2
    Lack of type safety
  • 2
    No built in support for parallelism (e.g. map-reduce)

related C lang posts

Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 15 upvotes · 1.2M views

Why Uber developed H3, our open source grid system to make geospatial data visualization and exploration easier and more efficient:

We decided to create H3 to combine the benefits of a hexagonal global grid system with a hierarchical indexing system. A global grid system usually requires at least two things: a map projection and a grid laid on top of the map. For map projection, we chose to use gnomonic projections centered on icosahedron faces. This projects from Earth as a sphere to an icosahedron, a twenty-sided platonic solid. The H3 grid is constructed by laying out 122 base cells over the Earth, with ten cells per face. H3 supports sixteen resolutions: https://eng.uber.com/h3/

(GitHub Pages : https://uber.github.io/h3/#/ Written in C w/ bindings in Java & JavaScript )

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One important decision for delivering a platform independent solution with low memory footprint and minimal dependencies was the choice of the programming language. We considered a few from Python (there was already a reasonably large Python code base at Thumbtack), to Go (we were taking our first steps with it), and even Rust (too immature at the time).

We ended up writing it in C. It was easy to meet all requirements with only one external dependency for implementing the web server, clearly no challenges running it on any of the Linux distributions we were maintaining, and arguably the implementation with the smallest memory footprint given the choices above.

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Apache Maven logo

Apache Maven

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Apache build manager for Java projects.
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PROS OF APACHE MAVEN
  • 136
    Dependency management
  • 71
    Necessary evil
  • 60
    I’d rather code my app, not my build
  • 48
    Publishing packaged artifacts
  • 43
    Convention over configuration
  • 18
    Modularisation
  • 11
    Consistency across builds
  • 6
    Prevents overengineering using scripting
  • 4
    Runs Tests
  • 4
    Lot of cool plugins
  • 3
    Extensible
  • 2
    Hard to customize
  • 2
    Runs on Linux
  • 1
    Runs on OS X
  • 1
    Slow incremental build
  • 1
    Inconsistent buillds
  • 1
    Undeterminisc
  • 1
    Good IDE tooling
CONS OF APACHE MAVEN
  • 6
    Complex
  • 1
    Inconsistent buillds
  • 0
    Not many plugin-alternatives

related Apache Maven posts

Tymoteusz Paul
Devops guy at X20X Development LTD · | 23 upvotes · 5.1M views

Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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Shared insights
on
Apache MavenApache MavenGradleGradle
at

We use Apache Maven because it is a standard. Gradle is very good alternative, but Gradle doesn't provide any advantage for our project. Gradle is slower (without running daemon), need more resources and a learning curve is quite big. Our project can not use a great flexibility of Gradle. On the other hand, Maven is well-know tool integrated in many IDEs, Dockers and so on.

See more
Scala logo

Scala

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A pure-bred object-oriented language that runs on the JVM
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PROS OF SCALA
  • 188
    Static typing
  • 179
    Pattern-matching
  • 177
    Jvm
  • 172
    Scala is fun
  • 138
    Types
  • 95
    Concurrency
  • 88
    Actor library
  • 86
    Solve functional problems
  • 83
    Open source
  • 80
    Solve concurrency in a safer way
  • 44
    Functional
  • 23
    Generics
  • 23
    Fast
  • 18
    It makes me a better engineer
  • 17
    Syntactic sugar
  • 13
    Scalable
  • 10
    First-class functions
  • 10
    Type safety
  • 9
    Interactive REPL
  • 8
    Expressive
  • 7
    SBT
  • 6
    Implicit parameters
  • 6
    Case classes
  • 4
    Used by Twitter
  • 4
    JVM, OOP and Functional programming, and static typing
  • 4
    Rapid and Safe Development using Functional Programming
  • 4
    Object-oriented
  • 3
    Functional Proframming
  • 2
    Spark
  • 2
    Beautiful Code
  • 2
    Safety
  • 2
    Growing Community
  • 1
    DSL
  • 1
    Rich Static Types System and great Concurrency support
  • 1
    Naturally enforce high code quality
  • 1
    Akka Streams
  • 1
    Akka
  • 1
    Reactive Streams
  • 1
    Easy embedded DSLs
  • 1
    Mill build tool
  • 0
    Freedom to choose the right tools for a job
CONS OF SCALA
  • 11
    Slow compilation time
  • 7
    Multiple ropes and styles to hang your self
  • 6
    Too few developers available
  • 4
    Complicated subtyping
  • 2
    My coworkers using scala are racist against other stuff

related Scala posts

Shared insights
on
JavaJavaScalaScalaApache SparkApache Spark

I am new to Apache Spark and Scala both. I am basically a Java developer and have around 10 years of experience in Java.

I wish to work on some Machine learning or AI tech stacks. Please assist me in the tech stack and help make a clear Road Map. Any feedback is welcome.

Technologies apart from Scala and Spark are also welcome. Please note that the tools should be relevant to Machine Learning or Artificial Intelligence.

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Marc Bollinger
Infra & Data Eng Manager at Thumbtack · | 5 upvotes · 505.1K views

Lumosity is home to the world's largest cognitive training database, a responsibility we take seriously. For most of the company's history, our analysis of user behavior and training data has been powered by an event stream--first a simple Node.js pub/sub app, then a heavyweight Ruby app with stronger durability. Both supported decent throughput and latency, but they lacked some major features supported by existing open-source alternatives: replaying existing messages (also lacking in most message queue-based solutions), scaling out many different readers for the same stream, the ability to leverage existing solutions for reading and writing, and possibly most importantly: the ability to hire someone externally who already had expertise.

We ultimately migrated to Kafka in early- to mid-2016, citing both industry trends in companies we'd talked to with similar durability and throughput needs, the extremely strong documentation and community. We pored over Kyle Kingsbury's Jepsen post (https://aphyr.com/posts/293-jepsen-Kafka), as well as Jay Kreps' follow-up (http://blog.empathybox.com/post/62279088548/a-few-notes-on-kafka-and-jepsen), talked at length with Confluent folks and community members, and still wound up running parallel systems for quite a long time, but ultimately, we've been very, very happy. Understanding the internals and proper levers takes some commitment, but it's taken very little maintenance once configured. Since then, the Confluent Platform community has grown and grown; we've gone from doing most development using custom Scala consumers and producers to being 60/40 Kafka Streams/Connects.

We originally looked into Storm / Heron , and we'd moved on from Redis pub/sub. Heron looks great, but we already had a programming model across services that was more akin to consuming a message consumers than required a topology of bolts, etc. Heron also had just come out while we were starting to migrate things, and the community momentum and direction of Kafka felt more substantial than the older Storm. If we were to start the process over again today, we might check out Pulsar , although the ecosystem is much younger.

To find out more, read our 2017 engineering blog post about the migration!

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Bazel logo

Bazel

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Build and test software of any size, quickly and reliably
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PROS OF BAZEL
  • 27
    Fast
  • 19
    Deterministic incremental builds
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    Correct
  • 15
    Multi-language
  • 13
    Enforces declared inputs/outputs
  • 9
    High-level build language
  • 8
    Scalable
  • 5
    Multi-platform support
  • 4
    Sandboxing
  • 3
    Dependency management
  • 2
    Flexible
  • 2
    Windows Support
  • 1
    Android Studio integration
CONS OF BAZEL
  • 3
    No Windows Support
  • 2
    Bad IntelliJ support
  • 1
    Poor windows support for some languages
  • 1
    Constant breaking changes
  • 1
    Learning Curve
  • 1
    Lack of Documentation

related Bazel posts

Joshua Dean Küpper
CEO at Scrayos UG (haftungsbeschränkt) · | 2 upvotes · 264.8K views

All Java-Projects are compiled using Apache Maven. We prefer it over Apache Ant and Gradle as it combines lightweightness with feature-richness and offers basically all we can imagine from a software project-management tool and more. We're open however to re-evaluate this decision in favor of Gradle or Bazel in the future if we feel like we're missing out on anything.

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Mill logo

Mill

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Simple, modern build tool for Scala and Java
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PROS OF MILL
    Be the first to leave a pro
    CONS OF MILL
      Be the first to leave a con

      related Mill posts

      CMake logo

      CMake

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      An open-source system that manages the build process
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      PROS OF CMAKE
      • 1
        Has package registry
      CONS OF CMAKE
        Be the first to leave a con

        related CMake posts

        Sonatype Nexus logo

        Sonatype Nexus

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        organize, store, and distribute software components
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        PROS OF SONATYPE NEXUS
          Be the first to leave a pro
          CONS OF SONATYPE NEXUS
            Be the first to leave a con

            related Sonatype Nexus posts

            Joshua Dean Küpper
            CEO at Scrayos UG (haftungsbeschränkt) · | 10 upvotes · 205.7K views

            We use Sonatype Nexus to store our closed-source java libraries to simplify our deployment and dependency-management. While there are many alternatives, most of them are expensive ( GitLab Enterprise ), monilithic ( JFrog Artifactory ) or only offer SaaS-licences. We preferred the on-premise approach of Nexus and therefore decided to use it.

            We exclusively use the Maven-capabilities and are glad that the modular design of Nexus allows us to run it very lightweight.

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            Bryan Dady
            SRE Manager at Subsplash · | 3 upvotes · 289K views

            I'm beginning to research the right way to better integrate how we achieve SCA / shift-left / SecureDevOps / secure software supply chain. If you use or have evaluated WhiteSource, Snyk, Sonatype Nexus, SonarQube or similar, I would very much appreciate your perspective on strengths and weaknesses and how you selected your ultimate solution. I want to integrate with GitLab CI.

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