Clojure vs Common Lisp: What are the differences?
Developers describe Clojure as "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. On the other hand, Common Lisp is detailed as "The modern, multi-paradigm, high-performance, compiled, ANSI-standardized descendant of the long-running family of Lisp programming languages". 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].
Clojure and Common Lisp can be categorized as "Languages" tools.
"It is a lisp" is the primary reason why developers consider Clojure over the competitors, whereas "Flexibility" was stated as the key factor in picking Common Lisp.
Clojure is an open source tool with 7.85K GitHub stars and 1.25K GitHub forks. Here's a link to Clojure's open source repository on GitHub.
According to the StackShare community, Clojure has a broader approval, being mentioned in 95 company stacks & 80 developers stacks; compared to Common Lisp, which is listed in 5 company stacks and 3 developer stacks.
What is Clojure?
What is Common Lisp?
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Stitch is run entirely on AWS. All of our transactional databases are run with Amazon RDS, and we rely on Amazon S3 for data persistence in various stages of our pipeline. Our product integrates with Amazon Redshift as a data destination, and we also use Redshift as an internal data warehouse (powered by Stitch, of course).
The majority of our services run on stateless Amazon EC2 instances that are managed by AWS OpsWorks. We recently introduced Kubernetes into our infrastructure to run the scheduled jobs that execute Singer code to extract data from various sources. Although we tend to be wary of shiny new toys, Kubernetes has proven to be a good fit for this problem, and its stability, strong community and helpful tooling have made it easy for us to incorporate into our operations.
I adopted Clojure and ClojureScript because:
- it's 1 language, multiple platforms.
- Simple syntax.
- Designed to avoid unwanted side effects and bugs.
- Immutable data-structures.
- Compact code, very expressive.
- Source code is data.
- It has super-flexible macro.
- Has metadata.
To complement Java. The REPL lets me interactively exercise Java code. I can write performant and safe libraries in Java, and then use them in Clojure. I also find the data-centric aspect of Clojure (excellent build-in structures, literal syntax for easily creating those structures, functions that act well on abstractions of those structures) good for data processing.
This fits a sweet spot between Ruby and Java.
We use Clojure mostly for its "Minority Report"-like interactive development in situations that require 'semi-automatic programming' (data inspection, admin tasks, API exploration, scrapers, etc.). We have also used Clojure successfully to build some components of our stack very quickly and reliably, in the backend and the frontend.
just started learning clojure, maybe around two weeks or so. i'm addicted. this is what i want to be working with and learning for the foreseeable future. the elegance of the language is refreshing. the community is really amazing. i've finally found a language that fits my passion for programming.
Clojure simplifies and reduces the coding efforts involved in creating CloudRepo. The fact that it runs in the JVM gives us access to all the libraries that we could ever need. Our code base is much smaller and easier to reason about than it would have been had we gone with pure Java.