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Spring Framework VS Hadoop

Compare Spring Framework VS Hadoop 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.

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing
  • Spring Framework Landing page
    Landing page //
    2023-08-18
  • Hadoop Landing page
    Landing page //
    2021-09-17

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.

Hadoop features and specs

  • Scalability
    Hadoop can easily scale from a single server to thousands of machines, each offering local computation and storage.
  • Cost-Effective
    It utilizes a distributed infrastructure, allowing you to use low-cost commodity hardware to store and process large datasets.
  • Fault Tolerance
    Hadoop automatically maintains multiple copies of all data and can automatically recover data on failure of nodes, ensuring high availability.
  • Flexibility
    It can process a wide variety of structured and unstructured data, including logs, images, audio, video, and more.
  • Parallel Processing
    Hadoop's MapReduce framework enables the parallel processing of large datasets across a distributed cluster.
  • Community Support
    As an Apache project, Hadoop has robust community support and a vast ecosystem of related tools and extensions.

Possible disadvantages of Hadoop

  • Complexity
    Setting up, maintaining, and tuning a Hadoop cluster can be complex and often requires specialized knowledge.
  • Overhead
    The MapReduce model can introduce additional overhead, particularly for tasks that require low-latency processing.
  • Security
    While improvements have been made, Hadoop's security model is considered less mature compared to some other data processing systems.
  • Hardware Requirements
    Though it can run on commodity hardware, Hadoop can still require significant computational and storage resources for larger datasets.
  • Lack of Real-Time Processing
    Hadoop is mainly designed for batch processing and is not well-suited for real-time data analytics, which can be a limitation for certain applications.
  • Data Integrity
    Distributed systems face challenges in maintaining data integrity and consistency, and Hadoop is no exception.

Spring Framework videos

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What is the Spring framework really all about?

More videos:

  • Tutorial - Spring Framework Tutorial | Full Course

Hadoop videos

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What is Big Data and Hadoop?

More videos:

  • Review - Product Ratings on Customer Reviews Using HADOOP.
  • Tutorial - Hadoop Tutorial For Beginners | Hadoop Ecosystem Explained in 20 min! - Frank Kane

Category Popularity

0-100% (relative to Spring Framework and Hadoop)

Spring Framework

Hadoop

Developer Tools
100 100%
Developer Tools
0% 0
Databases
0 0%
Databases
100% 100
Web Frameworks
100 100%
Web Frameworks
0% 0
Big Data
0 0%
Big Data
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 Hadoop

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

Hadoop Reviews

A List of The 16 Best ETL Tools And Why To Choose Them
Companies considering Hadoop should be aware of its costs. A significant portion of the cost of implementing Hadoop comes from the computing power required for processing and the expertise needed to maintain Hadoop ETL, rather than the tools or storage themselves.
Source: www.datacamp.com
16 Top Big Data Analytics Tools You Should Know About
Hadoop is an Apache open-source framework. Written in Java, Hadoop is an ecosystem of components that are primarily used to store, process, and analyze big data. The USP of Hadoop is it enables multiple types of analytic workloads to run on the same data, at the same time, and on a massive scale on industry-standard hardware.
Source: www.analytixlabs.co.in
5 Best-Performing Tools that Build Real-Time Data Pipeline
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than relying on hardware to deliver high-availability, the library itself is...
Source: www.analyticsinsight.net

Social recommendations and mentions

Based on our record, Hadoop should be more popular than Spring Framework. It has been mentiond 23 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 / about 2 months ago
  • Getting Started with Spring Boot 3 for .NET Developers
    Spring Framework 6: https://spring.io/projects/spring-framework. - Source: dev.to / 4 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 / over 2 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

Hadoop mentions (23)

  • India Open Source Development: Harnessing Collaborative Innovation for Global Impact
    Over the years, Indian developers have played increasingly vital roles in many international projects. From contributions to frameworks such as Kubernetes and Apache Hadoop to the emergence of homegrown platforms like OpenStack India, India has steadily carved out a global reputation as a powerhouse of open source talent. - Source: dev.to / 4 days ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / about 2 months ago
  • Apache Hadoop: Pioneering Open Source Innovation in Big Data
    Apache Hadoop is more than just software—it’s a full-fledged ecosystem built on the principles of open collaboration and decentralized governance. Born out of a need to process vast amounts of information efficiently, Hadoop uses a distributed file system and the MapReduce programming model to enable scalable, fault-tolerant computing. Central to its success is a diverse ecosystem that includes influential... - Source: dev.to / 2 months ago
  • Embracing the Future: India's Pioneering Journey in Open Source Development
    Navya: Designed to streamline administrative processes in educational institutions, Navya continues to demonstrate the power of open source in addressing local needs. Additionally, India’s vibrant tech communities are well represented on platforms like GitHub and SourceForge. These platforms host numerous Indian-led projects and serve as collaborative hubs for developers across diverse technology landscapes.... - Source: dev.to / 2 months ago
  • Where is Java Used in Industry?
    The rise of big data has seen Java arise as a crucial player in this domain. Tools like Hadoop and Apache Spark are built using Java, enabling businesses to process and analyze massive datasets efficiently. Java’s scalability and performance are critical for big data results that demand high trustability. - Source: dev.to / 5 months ago
View more

What are some alternatives?

When comparing Spring Framework and Hadoop, you can also consider the following products

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

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Django - The Web framework for perfectionists with deadlines

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Laravel - A PHP Framework For Web Artisans

Apache Storm - Apache Storm is a free and open source distributed realtime computation system.

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