Elasticsearch is an open source tool for searching and analysing various types of data. It is suitable for text, numerical, geospatial, structured and unstructured (NoSQL) data.
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Thanks to the use of a special data structure (so-called inverted index), it enables full-text search in almost real time.
The REST API can be used for many tasks, such as checking cluster status and performing index lookup operations.
The distributed nature of Elasticsearch allows you to scale hundreds to thousands of servers and process petabytes of data.
Elasticsearch recognises and discards false nodes in the cluster. Subsequently, the data are divided among the remaining nodes so that these are as accessible as possible.
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Elasticsearch receives data from a variety of sources, such as web applications, logs, or infrastructure information. Elasticsearch analyses and converts raw data into a normalised form so that it can be indexed. Subsequently, it is possible to search in them, analyse them and obtain comprehensive overviews and data summaries.
Elasticsearch index is an assignment for several elements that are interconnected and are stored as a JSON document. Each of the documents is then associated with a set of keys that characterise it. These keys take the form of numeric or Boolean values, a text string, geolocation, etc.
Elastic Stack is also referred to as ELK Stack based on the initials of its three components, which are Elasticsearch, Logstash and Kibana. While Elasticsearch works with the acquired data, Logstash provides aggregation and processing of data on the server side.
This makes it possible to receive data from multiple sources simultaneously and enrich it before indexing in Elasticsearch. Kibana, in turn, provides better visualisation and data management. It allows you to create not only common graphs and histograms, but also dynamic infographics or maps with visualisation of geospatial data.
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