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Spark Framework VS Python

Compare Spark Framework VS Python and see what are their differences

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Spark Framework logo Spark Framework

Spark Framework is a simple and lightweight Java web framework built for rapid development.

Python logo Python

Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
  • Spark Framework Landing page
    Landing page //
    2019-11-24
  • Python Landing page
    Landing page //
    2021-10-17

Spark Framework features and specs

  • Ease of Use
    Spark Framework provides a simple and intuitive API, making it easy to set up and run a web application with minimal configuration.
  • Lightweight
    Spark is very lightweight, which makes it well-suited for small applications and microservices where resource consumption is a concern.
  • Java 8 Lambda Support
    It supports Java 8 lambdas, allowing developers to write clean, readable, and more concise code.
  • Rapid Development
    The framework facilitates rapid development and prototyping, enabling developers to quickly build and iterate on ideas.
  • Minimal Configuration
    With less boilerplate code required, Spark allows developers to focus on business logic rather than intricate configurations.

Possible disadvantages of Spark Framework

  • Limited Ecosystem
    Compared to more established frameworks, Spark has a smaller ecosystem of plugins and extensions, which might limit functionality for larger projects.
  • Performance Overhead
    While suitable for small applications, the simplicity of Spark might introduce performance overhead when scaling up to larger, complex applications.
  • Concurrency Limitations
    Its concurrency model may not be robust enough for high-concurrency applications, potentially leading to scalability issues.
  • Less Community Support
    Spark's smaller user base means that community support and resources such as tutorials and forums are more limited compared to larger frameworks.
  • Basic Feature Set
    The framework offers a basic feature set, which may require additional coding or third-party libraries to achieve advanced functionalities.

Python features and specs

  • Easy to Learn
    Python syntax is clear and readable, which makes it an excellent choice for beginners and allows for quick learning and prototyping.
  • Versatile
    Python can be used for web development, data analytics, artificial intelligence, machine learning, automation, and more, making it a highly versatile programming language.
  • Large Standard Library
    Python comes with a comprehensive standard library that includes modules and packages for various tasks, reducing the need to write code from scratch.
  • Strong Community Support
    Python has a large and active community, which means a wealth of third-party packages, tutorials, and documentation is available for assistance.
  • Cross-Platform Compatibility
    Python is compatible with major operating systems like Windows, macOS, and Linux, allowing for easy development and deployment across different platforms.
  • Good for Rapid Development
    The high-level nature of Python allows for quick development cycles and fast iteration, which is ideal for startups and prototyping.

Possible disadvantages of Python

  • Performance Limitations
    Python is generally slower than compiled languages like C or Java because it is an interpreted language, which can be a drawback for performance-critical applications.
  • Global Interpreter Lock (GIL)
    The GIL in CPython, the most used Python interpreter, prevents multiple native threads from executing Python bytecodes at once, limiting multi-threading capabilities.
  • Memory Consumption
    Python can be more memory-intensive compared to some other languages, which might be a concern for applications with tight memory constraints.
  • Mobile Development
    Python is not a primary choice for mobile app development, where languages like Java, Swift, or Kotlin are more commonly used.
  • Runtime Errors
    Being a dynamically typed language, Python code can sometimes lead to runtime errors that would be caught at compile-time in statically typed languages.
  • Dependency Management
    Managing dependencies in Python projects can sometimes be complex and cumbersome, especially when dealing with conflicting versions of libraries.

Spark Framework videos

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Python videos

Creator of Python Programming Language, Guido van Rossum | Oxford Union

Category Popularity

0-100% (relative to Spark Framework and Python)
Web Frameworks
100 100%
0% 0
Programming Language
0 0%
100% 100
Developer Tools
100 100%
0% 0
OOP
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Spark Framework and Python

Spark Framework Reviews

17 Popular Java Frameworks for 2023: Pros, cons, and more
You can get the Spark Framework up and running in just a few minutes. By default, it runs on the Jetty web server that is embedded into the framework. However, you can use it with other Java web servers as well. According to Spark’s own survey, more than 50% of their users used the framework to create REST APIs, which is its most popular use case. Spark also powers...
Source: raygun.com

Python Reviews

Pine Script Alternatives: A Comprehensive Guide to Trading Indicator Languages
Technical analysis in trading has come a long way, with various programming languages emerging to support traders in developing custom indicators. While Pine Script has been a popular choice for many, alternatives like Indie, ThinkScript, NinjaScript, MetaQuotes Language (MQL), and even general-purpose languages like Python and C++ are gaining traction. Let’s explore these...
Source: medium.com
Top 5 Most Liked and Hated Programming Languages of 2022
No wonder Python is one of the easiest programming languages to work upon. This general-purpose programming language finds immense usage in the field of web development, machine learning applications, as well as cutting-edge technology in the software industry. The fact that Python is used by major tech giants such as Amazon, Facebook, Google, etc. is good enough proof as to...
Top 10 Rust Alternatives
This programming langue is typed statically and operates on a complied system. It works based on several computing languages Python, Ada, and Modula.
15 data science tools to consider using in 2021
Python is the most widely used programming language for data science and machine learning and one of the most popular languages overall. The Python open source project's website describes it as "an interpreted, object-oriented, high-level programming language with dynamic semantics," as well as built-in data structures and dynamic typing and binding capabilities. The site...
The 10 Best Programming Languages to Learn Today
Python's variety of applications make it a powerful and versatile language for different use cases. Python-based web development frameworks like Django and Flask are gaining popularity fast. It's also equipped with quality machine learning and data analysis tools like Scikit-learn and Pandas.
Source: ict.gov.ge

Social recommendations and mentions

Based on our record, Python should be more popular than Spark Framework. It has been mentiond 288 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Spark Framework mentions (29)

  • Indexing All of Wikipedia on a Laptop
    The code for serving queries is found in the WebSearch class. We’re using Spark (the web framework, not the big data engine) to serve a simple search form:. - Source: dev.to / 11 months ago
  • [ Servlet + JSP + JDBC ]
    Get a solid grasp of building web applications with Java either using Spring (using Spring Boot) or Spark (if you're also new to Java learning Java and Spring can be a mouthful). Instead of JSP use something Thymeleaf or build the frontend with HTML and JavaScript (and serve the bundles). Source: over 1 year ago
  • What's the language of the startup?
    So most of the "tech" stack goes out. In our first startup we created our own web-container by using https://sparkjava.com - and then built a JSR-223 scripting support. Source: over 1 year ago
  • What side-projects did you work on during your university years?
    Stack: Java, Spark (not the Apache Spark but this), Kafka, several other libraries like FasterXML's Jackson. Source: almost 2 years ago
  • Full Time
    The blog is just hugo so it's 100% static files over nginx. The search engine is serverside-rendered mustache templates via handlebars[1], via served via spark[2]. It's basically all vanilla Java. I do raw SQL queries instead of ORM, which makes it quite a bit snappier than most Java applications. The sheer size of the database also mandates that basically every query is a primary key lookup. The code is written... - Source: Hacker News / almost 2 years ago
View more

Python mentions (288)

  • A Beginner's Guide to Auto-Instrumenting a Flask App with OpenTelemetry and SigNoz
    If Python is not installed, download it from python.org or use your system's package manager (e.g., sudo apt install python3 on Ubuntu). - Source: dev.to / 28 days ago
  • Scraping Infinite Scroll Pages with a 'Load More' Button: A Step-by-Step Guide
    Python Installed: Download and install the latest Python version from python.org, including pip during setup. - Source: dev.to / 4 months ago
  • Get Started with Python
    First, you'll need to install Python if you don't have it already. Go to the official Python website python.org, download the latest version, and follow the instructions. - Source: dev.to / 5 months ago
  • Unlocking DuckDB from Anywhere - A Guide to Remote Access with Apache Arrow and Flight RPC (gRPC)
    Python: We’ll use Python for it’s simplicity and accessibility. - Source: dev.to / 5 months ago
  • Python Packaging is Great Now: `uv` is all you need
    Bootstrapping was an often neglected problem. Should we tell people to install Python from https://python.org? The Anaconda distribution? How do we stop folks from using their system package manager and risk breaking everything? - Source: dev.to / 9 months ago
View more

What are some alternatives?

When comparing Spark Framework and Python, you can also consider the following products

Javalin - Simple REST APIs for Java and Kotlin

JavaScript - Lightweight, interpreted, object-oriented language with first-class functions

vert.x - From Wikipedia, the free encyclopedia

Rust - A safe, concurrent, practical language

Micronaut Framework - Build modular easily testable microservice & serverless apps

Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible