Whether you’re trying to use big data to find insights regarding business decisions or to add new features and enhance the user experience, you need enterprise-level search to handle large volumes of data in a manageable period of time. Elasticsearch software collects unstructured data from web applications, log analytics, and system metrics before indexing the data so it may be retrieved via a search query. All search engines index data, but the scalability of Elastic allows for quick data ingestion on a grand scale, and a relevant search will return detailed information for complex queries. Different tools in the Elastic Stack can even return interactive visualizations of data.
A single index in the Elasticsearch engine is a collection of related documents or data. Elastic stores data in the form of JSON documents. Each of these JSON docs contains a key and a value (boolean, strings, geo data, etc.) is used in the Elastic data structure known as the inverted index. This allows for extremely fast searches by listing every unique word that appears in a document as well as how many documents have each unique word. Thanks to full API support, each JSON format document can be easily updated.
Elasticsearch data often comes from Logstash which is a server-side data aggregator that allows for simultaneous ingestion of multiple data sources. Kibana, a visualization and management tool in the Elastic Stack, can then be used to represent data via pie charts, line graphs, histograms, and other data visualizations.