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Spring Framework VS AWS Data Wrangler

Compare Spring Framework VS AWS Data Wrangler and see what are their differences

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Spring Framework logo Spring Framework

The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.

AWS Data Wrangler logo AWS Data Wrangler

Pandas on AWS. Contribute to awslabs/aws-data-wrangler development by creating an account on GitHub.
  • Spring Framework Landing page
    Landing page //
    2023-08-18
  • AWS Data Wrangler Landing page
    Landing page //
    2023-08-29

Spring Framework features and specs

  • Comprehensive Ecosystem
    Spring Framework provides a vast array of tools and modules which address various aspects of application development such as security, data access, and messaging. This helps in building robust enterprise applications.
  • Inversion of Control (IoC) Container
    Spring's IoC container promotes loose coupling by managing object lifecycles and dependencies, making the code more modular and testable.
  • Aspect-Oriented Programming (AOP)
    Spring's AOP module allows for separating cross-cutting concerns like logging, transaction management, and security, making the code cleaner and more maintainable.
  • Spring Boot
    Spring Boot streamlines the setup and development of new Spring applications with built-in configurations and convention over configuration, reducing boilerplate code and speeding up development time.
  • Large Community and Support
    Spring has a large and active community, extensive documentation, and a wide selection of online resources which make it easier to find support and solutions to common problems.
  • Integration Capabilities
    Spring Framework offers seamless integration with various other technologies and frameworks, including Hibernate for ORM, Apache Kafka for messaging, and more.

Possible disadvantages of Spring Framework

  • Complexity
    Spring Framework can be complex and have a steep learning curve, especially for newcomers who are not familiar with its extensive set of features and configurations.
  • Configuration Overhead
    Although Spring Boot reduces the configuration burden, traditional Spring applications may still require extensive XML or annotation-based configurations, which can be cumbersome.
  • Performance Overhead
    The flexibility and the modular nature of Spring can introduce some performance overhead compared to more lightweight solutions, which could be a concern in highly performance-sensitive applications.
  • Version Incompatibility
    Upgrading between different versions of the Spring Framework and its associated projects can sometimes lead to compatibility issues and necessitate significant code changes.
  • Dependency Management
    Managing dependencies in a large Spring application can become complicated, particularly when dealing with multiple modules and third-party libraries, potentially leading to dependency conflicts.

AWS Data Wrangler features and specs

No features have been listed yet.

Analysis of Spring Framework

Overall verdict

  • Yes, Spring Framework is generally considered a good framework with robust features, strong community support, and extensive documentation, making it a reliable choice for Java developers working on complex, enterprise-level applications.

Why this product is good

  • Features
    Spring provides a wide range of features including dependency injection, aspect-oriented programming, transaction management, and integration with various tools and technologies.
  • Community
    Spring has a large and active community, which contributes to a wealth of resources, documentation, and third-party extensions.
  • Popularity
    Spring Framework is one of the most popular frameworks for Java development, widely used in building enterprise applications.
  • Versatility
    It offers a comprehensive programming and configuration model for modern Java-based enterprise applications, on any kind of deployment platform.

Recommended for

  • Developers building large-scale, enterprise-grade applications.
  • Teams looking for a mature and well-supported framework with a large ecosystem.
  • Projects that require integration with popular Java technologies and tools.
  • Developers focusing on microservices architecture, as Spring Boot simplifies the development of microservices.

Spring Framework videos

+ Add

What is the Spring framework really all about?

More videos:

  • Tutorial - Spring Framework Tutorial | Full Course

AWS Data Wrangler videos

+ Add

AWS Tutorials - Introduction to AWS Data Wrangler

More videos:

  • Review - AWS Data Wrangler: Get Glue Catalog Table Description
  • Review - AWS Data Wrangler: Write Parquet to AWS S3

Category Popularity

0-100% (relative to Spring Framework and AWS Data Wrangler)

Spring Framework

AWS Data Wrangler

Developer Tools
100 100%
Developer Tools
0% 0
Databases
0 0%
Databases
100% 100
Web Frameworks
100 100%
Web Frameworks
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
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 Spring Framework and AWS Data Wrangler

Spring Framework Reviews

Top 9 best Frameworks for web development
Spring offers a wide range of frameworks, such as an MVC framework, a data access framework and a transaction management framework. With its focus on scalability and security, Spring is an excellent choice.
Source: www.kiwop.com
17 Popular Java Frameworks for 2023: Pros, cons, and more
Therefore, the configuration, setup, build, and deployment processes all require multiple steps you might not want to deal with, especially if you’re working on a smaller project. Spring Boot (a micro framework that runs on top of the Spring Framework) is a solution for this problem, as it allows you to set up your Spring application faster, with much less configuration.
Source: raygun.com
Top 10 Phoenix Framework Alternatives
Spring Framework is an open-source app framework and inversion of control container for the Java platform, providing the infrastructure required to develop Java and web apps on top of the Java EE platform.
Source: blog.back4app.com
10 Best Java Frameworks You Should Know
Spring Framework is one of the most extensively used, top-notch, lightweight software application frameworks built for software design, development, and deployment in Java.
Source: www.simplilearn.com

AWS Data Wrangler Reviews

We have no reviews of AWS Data Wrangler yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Spring Framework should be more popular than AWS Data Wrangler. It has been mentiond 13 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.

Spring Framework mentions (13)

  • March 2025 Java Key Updates in Boot, Security, and More
    The release of Spring Framework 6.2.5 includes:. - Source: dev.to / 3 months ago
  • Getting Started with Spring Boot 3 for .NET Developers
    Spring Framework 6: https://spring.io/projects/spring-framework. - Source: dev.to / 5 months ago
  • Want to Get Better at Java? Go Old School.
    We had to write our own frameworks (uphill, both ways) but most current frameworks will have similar documentation pages as well. Both Apache and Spring are especially good at that. - Source: dev.to / over 2 years ago
  • Best Frameworks For Web Development
    Framework link: https://spring.io/projects/spring-framework Github Link: https://github.com/spring-projects/spring-framework. - Source: dev.to / almost 3 years ago
  • What to you do now?
    A common used Java framework is Spring framework (ie https://spring.io/projects/spring-framework and short tutorials at https://www.baeldung.com/spring-intro). Source: almost 3 years ago
View more

AWS Data Wrangler mentions (4)

  • Read files from s3 using Pandas/s3fs or AWS Data Wrangler?
    I had no problem with awswrangler (https://github.com/aws/aws-sdk-pandas) and it supports reading and writing partitions which was really helpful and a few other optimizations that made it a great tool. Source: over 1 year ago
  • Redshift API vs. other ways to connect?
    Awslabs has developed their own package for this and given it's for their product, seem likely to maintain it. https://github.com/awslabs/aws-data-wrangler. Source: over 3 years ago
  • Parquet files
    AWS data wrangler works well. it's a wrapper on pandas: https://github.com/awslabs/aws-data-wrangler. Source: over 3 years ago
  • Go+: Go designed for data science
    Yep, agreed. Go is a great language for AWS Lambda type workflows. Python isn't as great (Python Lambda Layers built on Macs don't always work). AWS Data Wrangler (https://github.com/awslabs/aws-data-wrangler) provides pre-built layers, which is a work around, but something that's as portable as Go would be the best solution. - Source: Hacker News / about 4 years ago

What are some alternatives?

When comparing Spring Framework and AWS Data Wrangler, you can also consider the following products

Django - The Web framework for perfectionists with deadlines

nSpek - nSpek, build forms and mobile checklists without coding or developers. Canadian Digital Inspections and Form Builder Provider for Heavy Industries such as Mining and Construction.

Grails - An Open Source, full stack, web application framework for the JVM

Serverspec - Serverspec.github.com :

Laravel - A PHP Framework For Web Artisans

Dask - Dask natively scales Python Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love

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