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Elasticsearch

Elasticsearch is a powerful search and analytics engine. It's widely used for real-time data exploration and analysis, offering scalability and flexibility in handling large volumes of structured and unstructured data.

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  • What is Elasticsearch?

    Elasticsearch is an open-source search and analytics engine built on top of Apache Lucene. It is designed for scalable and real-time searching, storing, and analyzing large volumes of data. Elasticsearch is commonly used in applications requiring full-text search, log analytics, and business intelligence.

  • How does Elasticsearch handle data storage?

    Elasticsearch stores data in a distributed and schema-free JSON format. It uses a structure called an "index" to organize and manage the data. Each index consists of one or more shards, which are the basic units of scalability and parallelism.

  • What are the key features of Elasticsearch?

    Elasticsearch features include full-text search capabilities, real-time indexing, distributed search and analytics, support for various data types, scalability across clusters, and a RESTful API for easy integration with different applications.

  • How does Elasticsearch support full-text search?

    Elasticsearch uses an inverted index to support full-text search efficiently. It tokenizes and indexes the content of documents, allowing for quick and relevant search results. It supports complex queries, filtering, and aggregations to provide powerful search capabilities.

  • What is the role of Kibana in conjunction with Elasticsearch?

    Kibana is often used alongside Elasticsearch to visualize and explore data stored in Elasticsearch indices. It provides a user-friendly interface for creating dashboards, charts, and graphs, enabling users to interactively analyze and understand their data.

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