Clojure vs Scala

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Clojure

1.3K
1.2K
+ 1
1.1K
Scala

7.5K
5.7K
+ 1
1.5K
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Clojure vs Scala: What are the differences?

Clojure: A dynamic programming language that targets the Java Virtual Machine. Clojure is designed to be a general-purpose language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming. Clojure is a compiled language - it compiles directly to JVM bytecode, yet remains completely dynamic. Clojure is a dialect of Lisp, and shares with Lisp the code-as-data philosophy and a powerful macro system; Scala: A pure-bred object-oriented language that runs on the JVM. 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.

Clojure and Scala belong to "Languages" category of the tech stack.

"It is a lisp", "Concise syntax" and "Persistent data structures" are the key factors why developers consider Clojure; whereas "Static typing", "Jvm" and "Pattern-matching" are the primary reasons why Scala is favored.

Clojure and Scala are both open source tools. It seems that Scala with 11.8K GitHub stars and 2.75K forks on GitHub has more adoption than Clojure with 7.85K GitHub stars and 1.25K GitHub forks.

According to the StackShare community, Scala has a broader approval, being mentioned in 437 company stacks & 324 developers stacks; compared to Clojure, which is listed in 95 company stacks and 80 developer stacks.

Advice on Clojure and Scala
Needs advice
on
ScalaScalaNode.jsNode.js
and
GoGo

Finding the best server-side tool for building a personal information organizer that focuses on performance, simplicity, and scalability.

performance and scalability get a prototype going fast by keeping codebase simple find hosting that is affordable and scales well (Java/Scala-based ones might not be affordable)

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Replies (1)
David Annez
Head of Engineering at loveholidays · | 4 upvotes · 126.1K views

I've picked Node.js here but honestly it's a toss up between that and Go around this. It really depends on your background and skillset around "get something going fast" for one of these languages. Based on not knowing that I've suggested Node because it can be easier to prototype quickly and built right is performant enough. The scaffolding provided around Node.js services (Koa, Restify, NestJS) means you can get up and running pretty easily. It's important to note that the tooling surrounding this is good also, such as tracing, metrics et al (important when you're building production ready services).

You'll get more scalability and perf from go, but balancing them out I would say that you'll get pretty far with a well built Node.JS service (our entire site with over 1.5k requests/m scales easily and holds it's own with 4 pods in production.

Without knowing the scale you are building for and the systems you are using around it it's hard to say for certain this is the right route.

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Decisions about Clojure and Scala
Chose
PythonPython
over
ScalaScala

I am working in the domain of big data and machine learning. I am helping companies with bringing their machine learning models to the production. In many projects there is a tendency to port Python, PySpark code to Scala and Scala Spark.

This yields to longer time to market and a lot of mistakes due to necessity to understand and re-write the code. Also many libraries/apis that data scientists/machine learning practitioners use are not available in jvm ecosystem.

Simply, refactoring (if necessary) and organising the code of the data scientists by following best practices of software development is less error prone and faster comparing to re-write in Scala.

Pipeline orchestration tools such as Luigi/Airflow is python native and fits well to this picture.

I have heard some arguments against Python such as, it is slow, or it is hard to maintain due to its dynamically typed language. However cost/benefit of time consumed porting python code to java/scala alone would be enough as a counter-argument. ML pipelines rarerly contains a lot of code (if that is not the case, such as complex domain and significant amount of code, then scala would be a better fit).

In terms of performance, I did not see any issues with Python. It is not the fastest runtime around but ML applications are rarely time-critical (majority of them is batch based).

I still prefer Scala for developing APIs and for applications where the domain contains complex logic.

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We’re a new startup so we need to be able to deliver quick changes as we find our product market fit. We’ve also got to ensure that we’re moving money safely, and keeping perfect records. The technologies we’ve chosen mix mature but well maintained frameworks like Django, with modern web-first and api-first front ends like GraphQL, NextJS, and Chakra. We use a little Golang sparingly in our backend to ensure that when we interact with financial services, we do so with statically compiled, strongly typed, and strictly limited and reviewed code.

You can read all about it in our linked blog post.

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We needed to incorporate Big Data Framework for data stream analysis, specifically Apache Spark / Apache Storm. The three options of languages were most suitable for the job - Python, Java, Scala.

The winner was Python for the top of the class, high-performance data analysis libraries (NumPy, Pandas) written in C, quick learning curve, quick prototyping allowance, and a great connection with other future tools for machine learning as Tensorflow.

The whole code was shorter & more readable which made it easier to develop and maintain.

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Pros of Clojure
Pros of Scala
  • 116
    It is a lisp
  • 99
    Persistent data structures
  • 98
    Concise syntax
  • 88
    jvm-based language
  • 87
    Concurrency
  • 80
    Interactive repl
  • 75
    Code is data
  • 61
    Open source
  • 58
    Lazy data structures
  • 54
    Macros
  • 47
    Functional
  • 22
    Simplistic
  • 21
    Immutable by default
  • 19
    Excellent collections
  • 18
    Fast-growing community
  • 14
    Multiple host languages
  • 14
    Simple (not easy!)
  • 13
    Practical Lisp
  • 9
    Because it's really fun to use
  • 9
    Addictive
  • 9
    Community
  • 8
    It creates Reusable code
  • 8
    Web friendly
  • 8
    Rapid development
  • 7
    Minimalist
  • 5
    Java interop
  • 5
    Programmable programming language
  • 4
    Regained interest in programming
  • 3
    Compiles to JavaScript
  • 3
    EDN
  • 2
    Share a lot of code with clojurescript/use on frontend
  • 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

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Cons of Clojure
Cons of Scala
  • 9
    Cryptic stacktraces
  • 4
    Need to wrap basically every java lib
  • 3
    LISP!!!!!!!!
  • 3
    Good code heavily relies on local conventions
  • 3
    Toxic community
  • 2
    Slow application startup
  • 2
    Tonns of abandonware
  • 1
    Usable only with REPL
  • 1
    Hiring issues
  • 1
    Bad documented libs
  • 1
    Macros are overused by devs
  • 1
    Tricky profiling
  • 1
    IDE with high learning curve
  • 1
    Configuration bolierplate
  • 1
    Conservative community
  • 0
    Have no good and fast fmt
  • 11
    Slow compilation time
  • 6
    Multiple ropes and styles to hang your self
  • 4
    Too few developers available
  • 3
    Complicated subtyping
  • 2
    My coworkers using scala are racist against other stuff

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What is Clojure?

Clojure is designed to be a general-purpose language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming. Clojure is a compiled language - it compiles directly to JVM bytecode, yet remains completely dynamic. Clojure is a dialect of Lisp, and shares with Lisp the code-as-data philosophy and a powerful macro system.

What is 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.

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What companies use Clojure?
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What tools integrate with Clojure?
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Blog Posts

Aug 28 2019 at 3:10AM

Segment

PythonJavaAmazon S3+16
5
2143
DockerAmazon EC2Scala+8
6
2233
GitHubPythonGit+22
17
13459
GitHubGitDocker+34
29
40795
What are some alternatives to Clojure and Scala?
Haskell
It is a general purpose language that can be used in any domain and use case, it is ideally suited for proprietary business logic and data analysis, fast prototyping and enhancing existing software environments with correct code, performance and scalability.
Common Lisp
Lisp was originally created as a practical mathematical notation for computer programs, influenced by the notation of Alonzo Church's lambda calculus. It quickly became the favored programming language for artificial intelligence (AI) research. As one of the earliest programming languages, Lisp pioneered many ideas in computer science, including tree data structures, automatic storage management, dynamic typing, conditionals, higher-order functions, recursion, and the self-hosting compiler. [source: wikipedia]
Elixir
Elixir leverages the Erlang VM, known for running low-latency, distributed and fault-tolerant systems, while also being successfully used in web development and the embedded software domain.
Julia
Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.
Erlang
Some of Erlang's uses are in telecoms, banking, e-commerce, computer telephony and instant messaging. Erlang's runtime system has built-in support for concurrency, distribution and fault tolerance. OTP is set of Erlang libraries and design principles providing middle-ware to develop these systems.
See all alternatives