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Spring Batch vs Spring MVC: What are the differences?

Introduction

Spring Batch and Spring MVC are both frameworks used in Java-based application development. While Spring MVC is primarily used for building web applications, Spring Batch is designed for batch processing tasks. Although they are both part of the Spring Framework, there are key differences between them that should be considered when choosing the appropriate framework for a specific task.

  1. Architecture and Purpose: Spring MVC is an MVC (Model-View-Controller) framework used for building web applications. It follows a request/response architectural pattern, where incoming requests are handled by controllers, views render the response, and models provide data to views. On the other hand, Spring Batch is a framework specifically designed for batch processing. It provides reusable components for processing large volumes of data in a reliable, scalable, and fault-tolerant manner.

  2. Focus on Web Development vs Batch Processing: Spring MVC puts a strong emphasis on web development, providing features like request mapping, handling HTTP requests, and rendering views. It is suited for use cases where user interactions through web interfaces are the primary focus. On the contrary, Spring Batch focuses on processing large volumes of data in batch jobs, such as data extraction, transformation, and loading. It enables efficient processing of data without the need for user interactions.

  3. Transaction Management: In Spring MVC, transaction management is typically done using annotations or XML configuration files. It provides support for declarative transaction management with fine-grained control over transaction boundaries. Spring Batch, on the other hand, has built-in support for transaction management specifically for batch processing. It allows for chunk-oriented processing where a set number of items are processed in a single transaction.

  4. Scaling and Partitioning: Spring MVC supports handling HTTP requests in a distributed environment, but it does not provide built-in support for scaling or partitioning for batch processing. On the other hand, Spring Batch provides built-in features for scaling and partitioning batch jobs. It allows for parallel processing of large datasets by dividing them into smaller partitions and processing them concurrently.

  5. Monitoring and Job Execution: Spring MVC provides basic monitoring capabilities for HTTP requests and server metrics through various monitoring tools and frameworks. However, it does not provide specific monitoring features for batch jobs. In contrast, Spring Batch provides extensive monitoring features for batch jobs, including job launching, tracking, and management of job execution status and statistics.

  6. Error Handling and Retry: Spring MVC provides mechanisms for handling exceptions and errors in web applications. It allows for custom error handling, error pages, and exception mapping to appropriate responses. On the other hand, Spring Batch provides a comprehensive error handling and retry mechanism specifically designed for batch processing. It allows for configurable retries, skipping faulty items, and handling different types of errors encountered during batch processing.

In summary, Spring MVC is focused on web development and handles HTTP requests in an MVC pattern, while Spring Batch is specialized for batch processing tasks, providing features for transaction management, scaling, monitoring, and error handling tailored for such tasks.

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What is Spring Batch?

It is designed to enable the development of robust batch applications vital for the daily operations of enterprise systems. It also provides reusable functions that are essential in processing large volumes of records, including logging/tracing, transaction management, job processing statistics, job restart, skip, and resource management.

What is Spring MVC?

A Java framework that follows the Model-View-Controller design pattern and provides an elegant solution to use MVC in spring framework by the help of DispatcherServlet.

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What are some alternatives to Spring Batch and Spring MVC?
Hadoop
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets 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.
Talend
It is an open source software integration platform helps you in effortlessly turning data into business insights. It uses native code generation that lets you run your data pipelines seamlessly across all cloud providers and get optimized performance on all platforms.
Spring Boot
Spring Boot makes it easy to create stand-alone, production-grade Spring based Applications that you can "just run". We take an opinionated view of the Spring platform and third-party libraries so you can get started with minimum fuss. Most Spring Boot applications need very little Spring configuration.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Kafka
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
See all alternatives