Elastic-search
is a platform for distributed search and analysis of data in real time.
Its popularity is due to its ease of use, powerful features, and
scalability. Today I am going to brief about the advantages of using
elastic-search. It is as follows:
Elastic-search
What are Elastic-search Advantages
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- Schema Free
- Full text search
- Document oriented
- Rest full API Support
- Built on top of Lucene
- Elastic search is very fast
- DataBase: Mysql, postgress
- Elastic-search uses JSON objects as responses, which makes it possible to invoke
- Elastic-search server with a large number of different programming languages
- Elastic search is developed on Java, which makes it compatible on almost every platform
- Elastic search is real time, in other words after one second the added document is searchable in this engine
- Elastic-search supports almost every document type except those that do not support text rendering
- Elastic-search lets you perform and combine many types of searches — structured, unstructured, geo , metric — any way you want. Start simple with one question and see where it takes you
- It’s one thing to find the 10 best documents to match your query. But how do you make sense of, say, a billion log lines? Elastic-search aggregations let you zoom out to explore trends and patterns in your data
- Elastic search is distributed, which makes it easy to scale and integrate in any big organization. Creating full backups are easy by using the concept of gateway, which is present in Elastic-search. Handling multi-tenancy is very easy in Elastic-search when compared to Apache Solr
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