OpenSearch of search engine


OpenSearch is a distribution for search engines and log analysis, and is an open-source project forked from Elasticsearch and Kibana.

OpenSearch can be used for various purposes, such as implementing search functionality within websites or applications, log aggregation and analysis, monitoring, security auditing, and more, being utilized in many scenarios.

The OpenSearch project is actively developed and supported by the community. It provides a wide range of plugins and extensions, allowing users to customize it according to their needs.

The GitHub repository for OpenSearch can be found at the following URL:

OpenSearch OSS is an open-source software that combines search engine and analytics engine functionalities, developed as a fork of Elasticsearch. It is used in various software architectures for purposes such as:

  1. Search engine functionalities: OpenSearch OSS is used to implement search functionalities in various web applications like corporate websites or online shops. It can process large amounts of data quickly and execute flexible search queries, allowing users to find the desired information promptly.

  2. Log analysis and monitoring: OpenSearch OSS is used to collect and analyze vast amounts of log data such as server logs or application logs. Real-time log monitoring, aggregation, and visualization help in troubleshooting system issues and optimizing resources.

  3. Security information search: OpenSearch OSS is used to manage and search for security information and vulnerabilities in companies. By collecting information from multiple sources and executing appropriate queries, it can be utilized as a decision-making tool for security measures.

The benefits of using OpenSearch OSS include high scalability and flexibility. It can adapt flexibly to cloud environments and handle large-scale data processing, allowing for easy adaptation to system growth and changes. Being open-source, users can customize and extend it themselves, enabling the construction of search and analytics systems tailored to their needs.

OpenSearch OSS, as the open-source version of Elasticsearch, provides a fast and scalable search engine and data processing engine. OpenSearch offers tools and functionalities that enable the search, analysis, and visualization of large amounts of data.

The source code for OpenSearch is publicly available on GitHub and is divided into the following packages:

  1. opensearch-core: Contains the core functionalities of OpenSearch, such as query execution, data retrieval, and distributed processing.

  2. opensearch-dashboards: Includes features for visualization, dashboard creation, and tools for data visualization and analysis.

  3. opensearch-job-scheduler: Contains functionalities for scheduling jobs and batch processing to execute regular tasks.

  4. opensearch-sql: Provides functionalities for executing SQL queries to retrieve data.

  5. opensearch-security: Contains security-related functionalities, offering access control and authentication features.

The development team of OpenSearch regularly updates these packages, working collaboratively with the community to enhance functionalities and fix bugs. OpenSearch is widely used as a highly flexible and customizable search engine suitable for various use cases.

Distributed Search Engine

A distributed search engine refers to a search engine that adopts a mechanism to distribute and store information across multiple computers for processing. This allows for the scalable processing of large amounts of data.


A distributed search engine achieves load balancing and fault tolerance by distributing data among multiple nodes. When a user sends a search query, each node simultaneously performs a search and integrates the results to return them. This approach enables fast searching of large-scale data.


Distributed search engines are commonly implemented using open-source software (OSS) such as Apache Solr and Elasticsearch. These OSS provide functionalities for distributed processing and indexing, allowing the construction of a flexible and extensible search engine.

For example, Apache Solr is a fast and flexible full-text search engine based on Apache Lucene, demonstrating its power in processing large datasets. Elasticsearch, known as a distributed search engine, provides real-time search and analysis functionalities.

Distributed search engines are utilized to achieve high performance and availability in systems with large amounts of data or complex search requirements. As a result, they are widely used in various fields, including enterprises and research institutions.

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