When people ask, “what is Elasticsearch?”, some may answer that it’s “an index”, “a search engine”, an “analytics database”, “a big data solution”, that “it’s fast and scalable”, or that “it’s kind of like Google”. Depending on your level of familiarity with this technology, these answers may either bring you closer to an ah-ha moment or further confuse you. But the truth is, all of these answers are correct and that’s part of the appeal of Elasticsearch. Over the years, Elasticsearch and the ecosystem of components that’s grown around it called the “Elastic Stack” has been used for a growing number of use cases, from simple search on a website or document, collecting and analyzing log data, to a business intelligence tool for data analysis and visualization
Elasticsearch is a distributed, open-source search and analytics engine built on Apache Lucene and developed in Java. It started as a scalable version of the Lucene open-source search framework then added the ability to horizontally scale Lucene indices. Elasticsearch allows you to store, search, and analyze huge volumes of data quickly and in near real-time and give back answers in milliseconds. It’s able to achieve fast search responses because instead of searching the text directly, it searches an index. It uses a structure based on documents instead of tables and schemas and comes with extensive REST APIs for storing and searching the data. At its core, you can think of Elasticsearch as a server that can process JSON requests and give you back JSON data.
This is the best overview/starter point for those who are keen to learn about elasticsearch and kibana.
By the end of this course you should be able to interact with elasticsearch and tweak it to some extend.
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