Difference Between Hadoop and Elasticsearch
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:
|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.|