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Scala vs Scala Native: What are the differences?
Introduction:
Scala and Scala Native are both programming languages that are widely used in the software development industry. While they share some similarities, there are several key differences between the two.
1. Performance: One of the major differences between Scala and Scala Native is the performance they offer. Scala Native is designed to achieve faster runtime performance compared to Scala. Scala Native compiles the code directly to machine code, resulting in improved efficiency and reduced overhead.
2. Interoperability: Scala Native differs from Scala in terms of interoperability with other programming languages. While Scala is compatible with Java and can seamlessly use any Java libraries, Scala Native provides restricted interoperability with C and C++ libraries. This limitation can impact the availability of external libraries that can be used in Scala Native projects.
3. Memory Management: Scala and Scala Native handle memory management in different ways. Scala relies on the Java Virtual Machine (JVM) for memory management, where objects are stored in the heap and garbage collected. On the other hand, Scala Native utilizes manual memory management, allowing developers to directly manage memory allocation and deallocation. This can provide more control over memory usage but also requires more careful handling to avoid memory leaks and other issues.
4. Compilation Process: Another significant difference between Scala and Scala Native is the compilation process. Scala code is compiled into Java bytecode, which is then executed on the JVM. In contrast, Scala Native directly compiles code to machine code, resulting in faster execution and reduced dependency on the JVM.
5. Platform Support: Scala is well-supported on various platforms, including JVM, Android, and JavaScript through frameworks like Scala.js. However, Scala Native primarily focuses on native platforms, such as Linux, macOS, and other POSIX-compliant systems. This platform-centric approach of Scala Native makes it more suitable for system-level or low-level programming.
6. Ecosystem and Community: Scala has a larger and more mature ecosystem compared to Scala Native. Scala has been around for a longer time, and as a result, it has a larger community of developers, extensive documentation, and a wide range of libraries and frameworks available. Scala Native, being relatively new, has a smaller community and a more limited set of available libraries and resources.
In Summary, Scala Native offers better performance, limited interoperability, manual memory management, faster compilation process, platform support for native systems, and a smaller ecosystem compared to Scala.
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)
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.
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.
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.
Pros of Scala
- Static typing188
- Pattern-matching178
- Jvm175
- Scala is fun172
- Types138
- Concurrency95
- Actor library88
- Solve functional problems86
- Open source81
- Solve concurrency in a safer way80
- Functional44
- Fast24
- Generics23
- It makes me a better engineer18
- Syntactic sugar17
- Scalable13
- First-class functions10
- Type safety10
- Interactive REPL9
- Expressive8
- SBT7
- Case classes6
- Implicit parameters6
- Rapid and Safe Development using Functional Programming4
- JVM, OOP and Functional programming, and static typing4
- Object-oriented4
- Used by Twitter4
- Functional Proframming3
- Spark2
- Beautiful Code2
- Safety2
- Growing Community2
- DSL1
- Rich Static Types System and great Concurrency support1
- Naturally enforce high code quality1
- Akka Streams1
- Akka1
- Reactive Streams1
- Easy embedded DSLs1
- Mill build tool1
- Freedom to choose the right tools for a job0
Pros of Scala Native
- Scala is just much easier to program in than Rust1
- Interop with C libraries1
- Scala Native is fast and lightweight1
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Cons of Scala
- Slow compilation time11
- Multiple ropes and styles to hang your self7
- Too few developers available6
- Complicated subtyping4
- My coworkers using scala are racist against other stuff2
Cons of Scala Native
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What is Scala?
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