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:
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. |