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Table of contents
How does Elasticsearch work?
Uses of Elasticsearch
How does Open search work?
What is the Need to Create an Opensearch When we have Elasticsearch?
Features of Opensearch
Difference between Elasticsearch vs Opensearch
Companies that are Using Elasticsearch and Opensearch
Frequently Asked Questions
What is the role of ‘mapping’ in Elasticsearch or Opensearch?
Do the functionalities of Elasticsearch and OpenSearch overlap?
What variations in license do Elasticsearch and OpenSearch have?
What is Elasticsearch typically used for?
What are the advantages of Elasticsearch?
Last Updated: Mar 27, 2024

Elasticsearch vs Opensearch

Author Vidhi Sareen
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People frequently use Elasticsearch and Opensearch as tools for browsing and analyzing vast amounts of data. Elasticsearch enables you to store and organize enormous amounts of data, facilitating speedy searches and information retrieval. On the other hand, Opensearch has the same functionality as Elasticsearch.

Elasticsearch vs Opensearch

Elasticsearch and Opensearch, two well-known tools for data analysis, will be covered in this article. We'll also learn what differentiates them from one another.


Elasticsearch is a powerful tool for exploring and examining vast amounts of data. It is open-sourced and can be used on many computers simultaneously. Elasticsearch lets you save, find, and examine vast data and quickly get your desired answers.


Elasticsearch can quickly find information because it doesn't explore the text directly. Instead, it looks through an index. It is like a simplified version of the text. It manages data in a way that is easy to operate. Elasticsearch also has tools to keep and search data using REST APIs. You can imagine Elasticsearch as a server that understands and responds to requests written in JSON format.

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How does Elasticsearch work?

Elasticsearch is a super speedy search engine that helps us find data or information fast. Instead of reading the data directly, it arranges the information to speed up searching. The data is stored in unique structures. Each information is represented as a JSON document.


When we search for something, Elasticsearch looks through these organized structures, not the actual text, increasing the process's speed. The search results are arranged by importance or priority. The most crucial documents are placed at the top.

Developers can work with Elasticsearch using simple commands called RESTful APIs. They help in controlling the data. Elasticsearch is great because it can manage data that keeps changing constantly. It's great for apps that require the latest information. It can quickly process and include new data in the search, making it available immediately.

Uses of Elasticsearch

There are many uses of Elasticsearch, such as: 

  • Elasticsearch is widely used in big data scenarios for real-time indexing and searching.
  • It collects data into documents and can convert log files into a convenient storage format.
  • The system uses metrics to capture periodic counts of system implementation data, like CPU usage or memory utilization.
  • Elasticsearch's architecture is built to handle and manage massive data.
  • This advanced architecture permits efficient storage, indexing, and recovery of the extensive data stored in Elasticsearch.


OpenSearch is an open-source distributed search and analytics engine. It desires to show users Elasticsearch's capability and scalability without relying on a single corporate organization. It aims to provide a community-driven, open, and vendor-neutral alternative. OpenSearch is managed in a more inclusive and community-driven way. It retains most of Elasticsearch's features and functions. This ensure stability and compatibility for users in the long run.


How does Open search work?

OpenSearch is a search and analytics engine that enables efficient data management and analysis. It works through critical concepts like nodesclustersindexesshards, and documents

Nodes denote running instances of OpenSearch (having one instance per server is considered the best). Clusters are collections of nodes sharing the same name. In case of failure, they automatically select primary nodes that can be replaced. Indexes act as logical namespaces. They are similar to database tables. They are associated with primary and replica shards. Shards store individual documents. It contains primary shards splitting data for parallel querying. The replicas serve as redundant copies for failover and performance improvement.


Documents in OpenSearch are stored as JSON files and have related fields and values. The process involves:

  • Creating a cluster of nodes.
  • Defining indexes.
  • Indexing documents.
  • Using OpenSearch's powerful search abilities to conduct searches on the data.

What is the Need to Create an Opensearch When we have Elasticsearch?

OpenSearch was created because Elasticsearch changed its license to a restrictive one. OpenSearch aims to provide functionalities like Elasticsearch. It maintains a more permissive licensing approach. This ensures continued access to essential features for users who prefer open-source solutions.

Features of Opensearch

There are many uses of OpenSearch, such as:

  • OpenSearch is good at handling lots of information and search requests. It runs on multiple computers or nodes.
  • It works across clusters of nodes. It delivers backup and fault tolerance in case of server defeats. A cluster is a group of interconnected nodes that work together. Each cluster has a unique name. Nodes present within the cluster communicate with each other to maintain data consistency.
  • OpenSearch permits users to explore data and acquire insights through aggregations and metrics.
  • OpenSearch has unique built-in support like Transport Layer Security (TLS), Node-to-Node Encryption and Audit Logging. They keep data and contact safe using features like login, access control, and secret code.
  • OpenSearch has tools to monitor the health of clusters and set up alerts for possible issues.
  • OpenSearch is used in different use cases, like search engines, log analytics, and business intelligence.

Difference between Elasticsearch vs Opensearch

The difference between Elasticsearch and OpenSearch are:

Elasticsearch  OpenSearch
Elastic developed Elasticsearch in 2010. Opensearch is an open source fork of Elasticsearch and Kibana.
Elastic owns and maintains Elasticsearch. The Opensearch community governs and oversees its development.
Elasticsearch uses Server Side Public License. Opensearch is licensed under Apache 2.0.
Elasticsearch has established itself well with many integrations. It seeks compatibility and strives for growth.
Elasticsearch shares APIs and query languages. Opensearch aims to be compatible with Elasticsearch.
It evolves independently under the management of Elastic. It follows a community-driven development process.

Companies that are Using Elasticsearch and Opensearch

Many companies are using Elasticsearch, such as: 

  • Netflix: Netflix can provide content to millions of consumers worldwide efficiently. It can monitor real-time logs across its extensive infrastructure. Additionally, it can search and analyze these logs as well.
  • Red Hat: Red Hat uses OpenSearch for two main purposes. The first is to enhance log management. The second is to improve system monitoring in their corporate software. They achieve these goals by leveraging the capabilities of OpenSearch.
  • Uber: Uber uses Elasticsearch for several purposes. It helps them process and analyze massive volumes of data. This, in turn, enhances their ride-matching capabilities. It also improves ETA (Estimated Time of Arrival) forecasts. Additionally, Elasticsearch is important in improving both driver and rider experiences.
  • General Electric: General Electric (GE) integrates OpenSearch. They use it to follow and examine data from industrial machinery. This integration helps them improve maintenance practices. Additionally, it increases efficiency throughout their industrial infrastructure.
  • LinkedIn: LinkedIn's professional networking platform uses Elasticsearch. It offers millions of users quick and precise search results. These results are especially helpful for networking and job searches.
  • Cisco: Cisco incorporates Elasticsearch into its networking and security solutions. It is used to gather and analyze network data. Additionally, it supports maintenance and troubleshooting activities.

Frequently Asked Questions

What is the role of ‘mapping’ in Elasticsearch or Opensearch?

The ‘mapping’ defines a way in which documents are their fields are stored and indexed in Elasticsearch or Opensearch. It allows efficient searching and fast data retrieval operations.

Do the functionalities of Elasticsearch and OpenSearch overlap?

Yes, OpenSearch keeps the essential elements of Elasticsearch, such as scalable distributed search and RESTful API, and supports different data formats.

What variations in license do Elasticsearch and OpenSearch have?

OpenSearch is given under the Apache 2.0 license, which offers more flexibility and freedom than Elasticsearch, which uses the Elastic License with some usage restrictions.

What is Elasticsearch typically used for?

Applications where Elasticsearch is used include log analysis, e-commerce search, monitoring, content delivery, and powering search features in web applications.

What are the advantages of Elasticsearch?

Elasticsearch offers real-time analytics, diverse data kinds, quick search results, improves scalability, supports many different programming languages, and integrates with several other tools.


In this article, we will learn about Elasticsearch and OpenSearch. We have discussed the working of Elasticsearch in detail. We even explore different uses of Elasticsearch. We have also learned about OpenSearch. We even explore features that make Open search unique. We discuss the difference between Elasticsearch vs OpenSearch. In the end, we discuss what all the famous companies are using Elasticsearch and OpenSearch. 

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