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Difference Between Hadoop and Elasticsearch

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  • Difficulty Level : Easy
  • Last Updated : 13 Jul, 2021
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Hadoop: It is a framework that allows for the analysis of voluminous distributed data and its processing across clusters of computers in a fraction of seconds using simple programming models. It is designed for scaling a single server to that of multiple machines each offering local computation and storage. 

Easticsearch: It is an “Open Source, Distributed, RESTful Search Engine”. It is an analytic engine that has the capability of storing and searching voluminous data in near real-time. Elasticsearch, Kibana, Beats, and Logstash are the Elastic Stack (sometimes called the ELK Stack). 



Below is a table of differences between Hadoop and Elasticsearch: 


S.No. Elasticsearch Hadoop
1. It is an Open Source, Distributed, RESTful Search Engine It is an Open-source software for reliable, scalable, distributed computing
2. Primarily used as a search engine Used to analyze large volume of data
3. Based on REST architecture ad provides API endpoints to perform CRUD operations over HTTP. Follows master-slave architecture for storage and processing of data using HDFS and MapReduce programming.
4. Provides full query DSL based on JSON Uses MapReduce programming model for processing of huge data clusters.
5. Full text search engine but can also be used as analytics framework. Used as a tool to store data and run applications on clusters.
6. Supported in all Operating Systems with Java VM Supported in Linux, Unix and Windows.
7. SQL-Like query Language Uses Hive for query processing
8. Analytics on top of your search. Rich APIs for data transformation and preparing data in distributed environment without memory issues.


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