Alternatives to Vala logo

Alternatives to Vala

Java, D, C, Rust, and Python are the most popular alternatives and competitors to Vala.
21
16
+ 1
9

What is Vala and what are its top alternatives?

It is a programming language using modern high level abstractions without imposing additional runtime requirements and without using a different ABI compared to applications and libraries written in C.
Vala is a tool in the Languages category of a tech stack.

Top Alternatives to Vala

  • Java

    Java

    Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere! ...

  • D

    D

    D is a language with C-like syntax and static typing. It pragmatically combines efficiency, control, and modeling power, with safety and programmer productivity. ...

  • C

    C

  • Rust

    Rust

    Rust is a systems programming language that combines strong compile-time correctness guarantees with fast performance. It improves upon the ideas of other systems languages like C++ by providing guaranteed memory safety (no crashes, no data races) and complete control over the lifecycle of memory. ...

  • Python

    Python

    Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best. ...

  • Nim

    Nim

    It is an efficient, expressive and elegant language which compiles to C/C++/JS and more. It combines successful concepts from mature languages like Python, Ada and Modula. ...

  • Go

    Go

    Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language. ...

  • Qt

    Qt

    Qt, a leading cross-platform application and UI framework. With Qt, you can develop applications once and deploy to leading desktop, embedded & mobile targets. ...

Vala alternatives & related posts

Java logo

Java

91.3K
68.1K
3.6K
A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
91.3K
68.1K
+ 1
3.6K
PROS OF JAVA
  • 583
    Great libraries
  • 439
    Widely used
  • 398
    Excellent tooling
  • 385
    Huge amount of documentation available
  • 330
    Large pool of developers available
  • 203
    Open source
  • 198
    Excellent performance
  • 154
    Great development
  • 148
    Vast array of 3rd party libraries
  • 147
    Used for android
  • 59
    Compiled Language
  • 49
    Used for Web
  • 46
    Managed memory
  • 44
    High Performance
  • 44
    Native threads
  • 41
    Statically typed
  • 35
    Easy to read
  • 33
    Great Community
  • 29
    Reliable platform
  • 24
    Sturdy garbage collection
  • 24
    JVM compatibility
  • 21
    Cross Platform Enterprise Integration
  • 20
    Good amount of APIs
  • 20
    Universal platform
  • 18
    Great Support
  • 13
    Great ecosystem
  • 11
    Backward compatible
  • 11
    Lots of boilerplate
  • 10
    Everywhere
  • 9
    Excellent SDK - JDK
  • 7
    Static typing
  • 6
    Mature language thus stable systems
  • 6
    Portability
  • 6
    Cross-platform
  • 6
    Long term language
  • 6
    Better than Ruby
  • 6
    It's Java
  • 5
    Vast Collections Library
  • 5
    Clojure
  • 5
    Used for Android development
  • 4
    Most developers favorite
  • 4
    Old tech
  • 3
    Testable
  • 3
    Javadoc
  • 3
    Best martial for design
  • 3
    Great Structure
  • 3
    Stable platform, which many new languages depend on
  • 2
    History
CONS OF JAVA
  • 30
    Verbosity
  • 25
    NullpointerException
  • 16
    Overcomplexity is praised in community culture
  • 14
    Nightmare to Write
  • 11
    Boiler plate code
  • 8
    Classpath hell prior to Java 9
  • 6
    No REPL
  • 4
    No property
  • 2
    Floating-point errors
  • 2
    There is not optional parameter
  • 2
    Code are too long
  • 2
    Non-intuitive generic implementation
  • 1
    Returning Wildcard Types
  • 1
    Java's too statically, stronglly, and strictly typed
  • 1
    Terrbible compared to Python/Batch Perormence

related Java posts

Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 39 upvotes · 4.2M views

How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

https://eng.uber.com/distributed-tracing/

(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

See more
Kamil Kowalski
Lead Architect at Fresha · | 27 upvotes · 1.2M views

When you think about test automation, it’s crucial to make it everyone’s responsibility (not just QA Engineers'). We started with Selenium and Java, but with our platform revolving around Ruby, Elixir and JavaScript, QA Engineers were left alone to automate tests. Cypress was the answer, as we could switch to JS and simply involve more people from day one. There's a downside too, as it meant testing on Chrome only, but that was "good enough" for us + if really needed we can always cover some specific cases in a different way.

See more
D logo

D

103
112
145
Modern convenience. Modeling power. Native efficiency.
103
112
+ 1
145
PROS OF D
  • 15
    Compile-time function execution
  • 12
    Makes functional programming style easier
  • 11
    Powerful static function to avoid macro
  • 11
    Much easier to do Concurrent/Parallel vs C/C++
  • 11
    Productive
  • 10
    Simple but Powerful template-based generics
  • 9
    Meta program is much easier to read/write vs. C++
  • 9
    Supports code covarge directly in the compiler
  • 8
    Assembler is support directly in the language
  • 8
    System program language like C++ and C
  • 8
    It support unittest etc
  • 6
    Supports both manuel memory and garbage collection
  • 6
    Easy to translate from Java and C# to D
  • 6
    Metaprogramming
  • 5
    Plugs directly into C
  • 4
    Feels and looks like C, so it's easy to learn
  • 3
    Amazing developer productivity
  • 1
    Performance
  • 1
    Syntax uniformity across pre-compile/compile/runtime
  • 1
    Fast
CONS OF D
    Be the first to leave a con

    related D posts

    C logo

    C

    6.3K
    4K
    236
    One of the most widely used programming languages of all time
    6.3K
    4K
    + 1
    236
    PROS OF C
    • 66
      Performance
    • 47
      Low-level
    • 34
      Portability
    • 28
      Hardware level
    • 18
      Embedded apps
    • 12
      Pure
    • 9
      Performance of assembler
    • 7
      Ubiquity
    • 4
      Great for embedded
    • 4
      Old
    • 3
      Compiles quickly
    • 2
      OpenMP
    • 2
      No garbage collection to slow it down
    CONS OF C
    • 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 posts

    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 15 upvotes · 1.1M 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 )

    See more
    Shared insights
    on
    GoGoCCPythonPythonRustRust
    at

    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.

    See more
    Rust logo

    Rust

    2.8K
    3.2K
    1K
    A safe, concurrent, practical language
    2.8K
    3.2K
    + 1
    1K
    PROS OF RUST
    • 131
      Guaranteed memory safety
    • 118
      Fast
    • 76
      Open source
    • 72
      Minimal runtime
    • 64
      Pattern matching
    • 58
      Type inference
    • 53
      Algebraic data types
    • 50
      Concurrent
    • 44
      Efficient C bindings
    • 41
      Practical
    • 34
      Best advances in languages in 20 years
    • 27
      Fix for C/C++
    • 26
      Safe, fast, easy + friendly community
    • 20
      Closures
    • 20
      Stablity
    • 17
      Zero-cost abstractions
    • 15
      Extensive compiler checks
    • 14
      Great community
    • 12
      No NULL type
    • 11
      Completely cross platform: Windows, Linux, Android
    • 10
      No Garbage Collection
    • 10
      Async/await
    • 9
      Great documentations
    • 9
      Super fast
    • 9
      High-performance
    • 8
      High performance
    • 8
      Safety no runtime crashes
    • 7
      Generics
    • 7
      Fearless concurrency
    • 7
      Guaranteed thread data race safety
    • 6
      RLS provides great IDE support
    • 6
      Painless dependency management
    • 6
      Prevents data races
    • 6
      Easy Deployment
    • 6
      Helpful compiler
    • 6
      Compiler can generate Webassembly
    • 5
      Macros
    • 3
      Real multithreading
    • 2
      Good package management
    • 2
      Support on Other Languages
    CONS OF RUST
    • 24
      Hard to learn
    • 22
      Ownership learning curve
    • 8
      Unfriendly, verbose syntax
    • 3
      Many type operations make it difficult to follow
    • 3
      High size of builded executable
    • 3
      Variable shadowing
    • 2
      No jobs

    related Rust posts

    James Cunningham
    Operations Engineer at Sentry · | 18 upvotes · 110.7K views
    Shared insights
    on
    PythonPythonRustRust
    at

    Sentry's event processing pipeline, which is responsible for handling all of the ingested event data that makes it through to our offline task processing, is written primarily in Python.

    For particularly intense code paths, like our source map processing pipeline, we have begun re-writing those bits in Rust. Rust’s lack of garbage collection makes it a particularly convenient language for embedding in Python. It allows us to easily build a Python extension where all memory is managed from the Python side (if the Python wrapper gets collected by the Python GC we clean up the Rust object as well).

    See more
    Jakub Olan
    Node.js Software Engineer · | 17 upvotes · 253.9K views

    In our company we have think a lot about languages that we're willing to use, there we have considering Java, Python and C++ . All of there languages are old and well developed at fact but that's not ideology of araclx. We've choose a edge technologies such as Node.js , Rust , Kotlin and Go as our programming languages which is some kind of fun. Node.js is one of biggest trends of 2019, same for Go. We want to grow in our company with growth of languages we have choose, and probably when we would choose Java that would be almost impossible because larger languages move on today's market slower, and cannot have big changes.

    See more
    Python logo

    Python

    151.6K
    124.1K
    6.5K
    A clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
    151.6K
    124.1K
    + 1
    6.5K
    PROS OF PYTHON
    • 1.1K
      Great libraries
    • 933
      Readable code
    • 824
      Beautiful code
    • 772
      Rapid development
    • 674
      Large community
    • 420
      Open source
    • 380
      Elegant
    • 270
      Great community
    • 262
      Object oriented
    • 209
      Dynamic typing
    • 71
      Great standard library
    • 53
      Very fast
    • 50
      Functional programming
    • 37
      Scientific computing
    • 36
      Easy to learn
    • 31
      Great documentation
    • 25
      Matlab alternative
    • 23
      Productivity
    • 23
      Easy to read
    • 20
      Simple is better than complex
    • 18
      It's the way I think
    • 17
      Imperative
    • 15
      Very programmer and non-programmer friendly
    • 15
      Free
    • 14
      Powerfull language
    • 14
      Powerful
    • 13
      Fast and simple
    • 12
      Scripting
    • 11
      Machine learning support
    • 9
      Explicit is better than implicit
    • 8
      Ease of development
    • 8
      Unlimited power
    • 8
      Clear and easy and powerfull
    • 7
      Import antigravity
    • 6
      Print "life is short, use python"
    • 6
      It's lean and fun to code
    • 5
      Fast coding and good for competitions
    • 5
      Flat is better than nested
    • 5
      There should be one-- and preferably only one --obvious
    • 5
      Python has great libraries for data processing
    • 5
      High Documented language
    • 5
      I love snakes
    • 5
      Although practicality beats purity
    • 5
      Great for tooling
    • 4
      Readability counts
    • 3
      Plotting
    • 3
      CG industry needs
    • 3
      Beautiful is better than ugly
    • 3
      Complex is better than complicated
    • 3
      Great for analytics
    • 3
      Multiple Inheritence
    • 3
      Now is better than never
    • 3
      Lists, tuples, dictionaries
    • 3
      Rapid Prototyping
    • 3
      Socially engaged community
    • 2
      List comprehensions
    • 2
      Web scraping
    • 2
      Many types of collections
    • 2
      Ys
    • 2
      Easy to setup and run smooth
    • 2
      Generators
    • 2
      Special cases aren't special enough to break the rules
    • 2
      If the implementation is hard to explain, it's a bad id
    • 2
      If the implementation is easy to explain, it may be a g
    • 2
      Simple and easy to learn
    • 2
      Import this
    • 2
      No cruft
    • 2
      Easy to learn and use
    • 1
      Better outcome
    • 1
      It is Very easy , simple and will you be love programmi
    • 1
      Powerful language for AI
    • 1
      Should START with this but not STICK with This
    • 1
      Flexible and easy
    • 1
      Batteries included
    • 1
      Good
    • 1
      A-to-Z
    • 1
      Only one way to do it
    • 1
      Because of Netflix
    • 1
      Pip install everything
    • 0
      Powerful
    • 0
      Pro
    CONS OF PYTHON
    • 51
      Still divided between python 2 and python 3
    • 29
      Performance impact
    • 26
      Poor syntax for anonymous functions
    • 21
      GIL
    • 19
      Package management is a mess
    • 14
      Too imperative-oriented
    • 12
      Dynamic typing
    • 12
      Hard to understand
    • 10
      Very slow
    • 8
      Not everything is expression
    • 7
      Indentations matter a lot
    • 7
      Explicit self parameter in methods
    • 6
      No anonymous functions
    • 6
      Poor DSL capabilities
    • 6
      Incredibly slow
    • 6
      Requires C functions for dynamic modules
    • 5
      The "lisp style" whitespaces
    • 5
      Fake object-oriented programming
    • 5
      Hard to obfuscate
    • 5
      Threading
    • 4
      Circular import
    • 4
      The benevolent-dictator-for-life quit
    • 4
      Official documentation is unclear.
    • 4
      Lack of Syntax Sugar leads to "the pyramid of doom"
    • 4
      Not suitable for autocomplete
    • 2
      Meta classes
    • 1
      Training wheels (forced indentation)

    related Python posts

    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 39 upvotes · 4.2M views

    How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

    Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

    Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

    https://eng.uber.com/distributed-tracing/

    (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

    Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

    See more
    Nick Parsons
    Director of Developer Marketing at Stream · | 35 upvotes · 1.4M views

    Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.

    We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)

    We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.

    Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.

    #FrameworksFullStack #Languages

    See more
    Nim logo

    Nim

    79
    111
    56
    A statically typed compiled systems programming language
    79
    111
    + 1
    56
    PROS OF NIM
    • 14
      Extremely fast
    • 13
      Expressive like Python
    • 11
      Very fast compilation
    • 5
      Cross platform
    • 5
      Macros
    • 4
      Optional garbage collection
    • 3
      Easy C interoperability
    • 1
      Adad
    CONS OF NIM
    • 4
      Small Community
    • 0
      [object Object]

    related Nim posts

    Go logo

    Go

    13.8K
    11.4K
    3.1K
    An open source programming language that makes it easy to build simple, reliable, and efficient software
    13.8K
    11.4K
    + 1
    3.1K
    PROS OF GO
    • 528
      High-performance
    • 385
      Simple, minimal syntax
    • 350
      Fun to write
    • 293
      Easy concurrency support via goroutines
    • 265
      Fast compilation times
    • 186
      Goroutines
    • 176
      Statically linked binaries that are simple to deploy
    • 146
      Simple compile build/run procedures
    • 132
      Backed by google
    • 129
      Great community
    • 48
      Garbage collection built-in
    • 40
      Built-in Testing
    • 39
      Excellent tools - gofmt, godoc etc
    • 36
      Elegant and concise like Python, fast like C
    • 32
      Awesome to Develop
    • 24
      Used for Docker
    • 23
      Flexible interface system
    • 21
      Great concurrency pattern
    • 21
      Deploy as executable
    • 18
      Open-source Integration
    • 15
      Fun to write and so many feature out of the box
    • 14
      Easy to read
    • 13
      Go is God
    • 13
      Its Simple and Heavy duty
    • 12
      Easy to deploy
    • 12
      Powerful and simple
    • 10
      Best language for concurrency
    • 10
      Concurrency
    • 9
      Rich standard library
    • 9
      Safe GOTOs
    • 8
      Clean code, high performance
    • 8
      Easy setup
    • 7
      High performance
    • 7
      Hassle free deployment
    • 7
      Simplicity, Concurrency, Performance
    • 6
      Used by Giants of the industry
    • 6
      Single binary avoids library dependency issues
    • 5
      Cross compiling
    • 5
      Simple, powerful, and great performance
    • 4
      Excellent tooling
    • 4
      WYSIWYG
    • 4
      Very sophisticated syntax
    • 4
      Gofmt
    • 4
      Garbage Collection
    • 3
      Kubernetes written on Go
    • 2
      Keep it simple and stupid
    • 2
      Widely used
    • 0
      No generics
    • 0
      Operator goto
    CONS OF GO
    • 41
      You waste time in plumbing code catching errors
    • 25
      Verbose
    • 22
      Packages and their path dependencies are braindead
    • 15
      Dependency management when working on multiple projects
    • 14
      Google's documentations aren't beginer friendly
    • 10
      Automatic garbage collection overheads
    • 8
      Uncommon syntax
    • 6
      Type system is lacking (no generics, etc)
    • 2
      Collection framework is lacking (list, set, map)

    related Go posts

    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber · | 39 upvotes · 4.2M views

    How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

    Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

    Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

    https://eng.uber.com/distributed-tracing/

    (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

    Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

    See more
    Nick Parsons
    Director of Developer Marketing at Stream · | 35 upvotes · 1.4M views

    Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.

    We chose JavaScript because nearly every developer knows or can, at the very least, read JavaScript. With ES6 and Node.js v10.x.x, it’s become a very capable language. Async/Await is powerful and easy to use (Async/Await vs Promises). Babel allows us to experiment with next-generation JavaScript (features that are not in the official JavaScript spec yet). Yarn allows us to consistently install packages quickly (and is filled with tons of new tricks)

    We’re using JavaScript for everything – both front and backend. Most of our team is experienced with Go and Python, so Node was not an obvious choice for this app.

    Sure... there will be haters who refuse to acknowledge that there is anything remotely positive about JavaScript (there are even rants on Hacker News about Node.js); however, without writing completely in JavaScript, we would not have seen the results we did.

    #FrameworksFullStack #Languages

    See more
    Qt logo

    Qt

    331
    446
    74
    A leading cross-platform application and UI framework
    331
    446
    + 1
    74
    PROS OF QT
    • 11
      High Performance
    • 9
      Declarative, easy and flexible UI
    • 9
      Performance
    • 8
      Cross platform
    • 6
      Up to date framework
    • 6
      Easiest integration with C++
    • 6
      Fast prototyping
    • 4
      Safe 2D Renderer
    • 4
      Python
    • 3
      Multiple license including Open Source and Commercial
    • 3
      Great Community Support
    • 3
      HW Accelerated UI
    • 2
      JIT and QML Compiler
    • 0
      Game Engine like UI system
    • 0
      From high to low level coding
    • 0
      Easy Integrating to DX and OpenGL and Vulkan
    • 0
      True cross-platform framework with native code compile
    • 0
      Been using it since the 90s - runs anywhere does it all
    • 0
      Great mobile support with Felgo add-on
    CONS OF QT
    • 4
      Paid
    • 4
      C++ is not so productive
    • 1
      Lack of libraries
    • 1
      Not detailed documentation
    • 1
      Lack of community support

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