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Hadoop vs Spring Batch: What are the differences?

Hadoop: Open-source software for reliable, scalable, distributed computing. 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; Spring Batch: A lightweight, comprehensive batch framework. 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..

Hadoop belongs to "Databases" category of the tech stack, while Spring Batch can be primarily classified under "Frameworks (Full Stack)".

Hadoop and Spring Batch are both open source tools. It seems that Hadoop with 9.27K GitHub stars and 5.78K forks on GitHub has more adoption than Spring Batch with 1.3K GitHub stars and 1.3K GitHub forks.

What is 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.

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.
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        What are some alternatives to Hadoop and Spring Batch?
        Cassandra
        Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
        MongoDB
        MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
        Elasticsearch
        Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
        Splunk
        Splunk Inc. provides the leading platform for Operational Intelligence. Customers use Splunk to search, monitor, analyze and visualize machine data.
        HBase
        Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
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        Decisions about Hadoop and Spring Batch
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        How developers use Hadoop and Spring Batch
        Avatar of Pinterest
        Pinterest uses HadoopHadoop

        The MapReduce workflow starts to process experiment data nightly when data of the previous day is copied over from Kafka. At this time, all the raw log requests are transformed into meaningful experiment results and in-depth analysis. To populate experiment data for the dashboard, we have around 50 jobs running to do all the calculations and transforms of data.

        Avatar of Yelp
        Yelp uses HadoopHadoop

        in 2009 we open sourced mrjob, which allows any engineer to write a MapReduce job without contending for resources. We’re only limited by the amount of machines in an Amazon data center (which is an issue we’ve rarely encountered).

        Avatar of Pinterest
        Pinterest uses HadoopHadoop

        The massive volume of discovery data that powers Pinterest and enables people to save Pins, create boards and follow other users, is generated through daily Hadoop jobs...

        Avatar of Robert Brown
        Robert Brown uses HadoopHadoop

        Importing/Exporting data, interpreting results. Possible integration with SAS

        Avatar of Rohith Nandakumar
        Rohith Nandakumar uses HadoopHadoop

        TBD. Good to have I think. Analytics on loads of data, recommendations?

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