Reliably And Securely Take Data And Search, Analyze, And Visualize It In Real Time.
Elasticsearch, Kibana, Beats, and Logstash (also known as the ELK Stack). Reliably and securely take data from any source, in any format, then search, analyze, and visualize it in real time.
Elasticsearch is used in a wide range of applications, including e-commerce, social media, cybersecurity, and data analytics. Its flexibility and scalability make it a popular choice for organizations that need to store and search large volumes of data in real time.
Elasticsearch can store and search a wide range of data types, including text, numerical, geospatial, and structured data. It is designed to be flexible and can be used to index and search almost any type of data.
Elasticsearch is a search engine and not a relational database. It is designed to handle unstructured and semi-structured data, whereas traditional databases are designed for structured data. Elasticsearch provides powerful search capabilities and can be used for text search, geospatial search, and more.
Yes, Elasticsearch is designed to handle large volumes of data. It is a distributed system that can scale horizontally by adding more nodes to the cluster. Elasticsearch is used by organizations to store and search billions of documents.
Elasticsearch uses a query language called the Elasticsearch Query DSL to perform search queries. The Query DSL is a JSON-based syntax that allows users to specify the search criteria and filters.
The ELK stack is a combination of Elasticsearch, Logstash, and Kibana. Logstash is used to collect and transform data from various sources, which is then indexed and stored in Elasticsearch. Kibana is used to visualize and analyze the data stored in Elasticsearch.
Yes, Elasticsearch is open source software that is distributed under the Apache License 2.0. The source code is available on GitHub.
Yes, Elasticsearch can be used for real-time analytics. It provides near real-time search capabilities and supports complex data analytics, such as aggregations and data visualization.
Elasticsearch and Solr are both search engines based on the Lucene search library. However, Elasticsearch is designed to be more scalable and easier to use, whereas Solr is designed to be more customizable. Elasticsearch is also more focused on near real-time search and analytics, whereas Solr is more focused on traditional search applications.
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, .NET (C#), PHP, Python, Ruby and many other languages. According to the DB-Engines ranking, Elasticsearch is the most popular enterprise search engine.