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Elasticsearch is a search engine based on Apache Lucene. It provides a distributed, multitenant -capable full-text search engine with an HTTP web interface and schema-free JSON documents. Official clients are available in Java , [ 2 ] .NET [ 3 ] ( C# ), PHP , [ 4 ] Python , [ 5 ] Ruby [ 6 ] and many other languages. [ 7 ]
After Solr 1.4, the next release of Solr was labeled 3.1, in order to keep Solr and Lucene on the same version number. [11] In October 2012, Solr version 4.0 was released, including the new SolrCloud feature. [12] 2013 and 2014 saw a number of Solr releases in the 4.x line, steadily growing the feature set and improving reliability.
OpenSearch is a Lucene-based search engine that started as a fork of version 7.10.2 of the Elasticsearch service. [8] [2] It has Elastic NV trademarks and telemetry removed. It is licensed under the Apache License, version 2, [2] without a Contributor License Agreement. The maintainers have made a commitment to remain completely compatible with ...
Comparison of programming languages; General comparison; Assignment; Basic syntax; Basic instructions; Comments; Control flow Foreach loops; While loops; For loops
Apache Solr – an enterprise search server; CrateDB – open source, distributed SQL database built on Lucene [15] DocFetcher – a multiplatform desktop search application [citation needed] Elasticsearch – an enterprise search server released in 2010 [16] [17] Kinosearch – a search engine written in Perl and C [18] and a loose port of ...
The combination of Elasticsearch, Logstash, and Kibana, referred to as the "Elastic Stack" (formerly the "ELK stack"), is available as a product or service. [6] Logstash provides an input stream to Elasticsearch for storage and search, and Kibana accesses the data for visualizations such as dashboards. [ 7 ]
In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database.Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases (such as titles, abstracts, selected sections, or bibliographical references).
The Open Semantic Framework (OSF) is an integrated software stack using semantic technologies for knowledge management. [1] It has a layered architecture that combines existing open source software with additional open source components developed specifically to provide a complete Web application framework.