Software Alternatives, Accelerators & Startups

ElasticSearch VS OpenSearch

Compare ElasticSearch VS OpenSearch and see what are their differences

ElasticSearch logo ElasticSearch

Elasticsearch is an open source, distributed, RESTful search engine.

OpenSearch logo OpenSearch

OpenSearch is a community-driven, open source search and analytics suite derived from Apache 2.0 licensed Elasticsearch 7.10.2 & Kibana 7.10.2. It consists of a search engine daemon, and a visualization and user interface, OpenSearch Dashboards.
  • ElasticSearch Landing page
    Landing page //
    2023-10-10
  • OpenSearch Landing page
    Landing page //
    2023-08-18

ElasticSearch features and specs

  • Scalability
    ElasticSearch is highly scalable, allowing you to handle large volumes of data and distribute indexing and search tasks across multiple nodes.
  • Real-Time Data
    It provides real-time indexing and searching capabilities, making it suitable for applications that require up-to-the-minute data retrieval and analysis.
  • Full-Text Search
    ElasticSearch is well-known for its powerful full-text search capabilities, enabling complex search queries and supporting a wide range of search options.
  • Complex Query Support
    It offers a rich query language allowing for complex and nested searching with filters, aggregations, and more.
  • Distributed Architecture
    ElasticSearch is designed to be distributed by nature, making it resilient to node failures and allowing data and search requests to be distributed across a cluster.
  • Open Source
    ElasticSearch is open-source, offering flexibility and a large community of developers that contribute to its continuous improvement and support.
  • Analytics
    Besides search, it also supports powerful analytics and visualization tools, especially when integrated with Kibana, its visualization dashboard.
  • Integrations
    ElasticSearch can easily integrate with various data sources and frameworks, enhancing its usability across different applications.

Possible disadvantages of ElasticSearch

  • Complexity
    Operating ElasticSearch can be complex, particularly when dealing with large-scale deployments, requiring specialized knowledge and expertise.
  • Resource Intensive
    ElasticSearch can be resource-intensive, requiring significant amounts of RAM and CPU, which can be costly for large-scale operations.
  • Consistency
    As a distributed system, ElasticSearch can sometimes face consistency issues, especially in scenarios involving partitions or network failures.
  • Security
    Though security features are available, they often require additional configurations and are more robust in the paid versions, which can be a concern for open-source users.
  • Cost
    While the core ElasticSearch software is open-source, scaling and additional features (like security, monitoring, and machine learning) are part of the paid Elastic Stack offerings.
  • Learning Curve
    There is a steep learning curve associated with mastering ElasticSearch and its query DSL (Domain Specific Language), which can be a barrier for new users.
  • Maintenance
    Properly maintaining an ElasticSearch cluster requires ongoing management, monitoring, and tuning to ensure optimal performance.
  • Backup and Restore
    Managing backups and restores can be cumbersome and is not as straightforward as in some other databases or data storage solutions.

OpenSearch features and specs

  • Open Source
    OpenSearch is released under the Apache 2.0 License, allowing users to freely use, modify, and distribute the software without licensing fees.
  • Elasticsearch Compatibility
    OpenSearch maintains compatibility with popular Elasticsearch features and APIs, allowing for seamless integration for those familiar with Elasticsearch.
  • Community Driven Development
    As an open-source project, it encourages community contributions and feedback, leading to rapid innovation and a diverse set of features.
  • Enhanced Security Features
    OpenSearch includes built-in security features like authentication, encryption, and role-based access control out of the box.
  • Comprehensive Visualization Tools
    The OpenSearch Dashboards offer extensive data visualization tools that are comparable to and compatible with Kibana, making it easier to explore and visualize data.

Possible disadvantages of OpenSearch

  • Relatively New Project
    Being a newer project compared to Elasticsearch, OpenSearch might have less maturity in certain advanced features or optimizations.
  • Smaller Community
    While growing, the OpenSearch community is smaller compared to Elasticsearch, potentially offering less community support or fewer third-party plugins.
  • Potential Steeper Learning Curve
    For users switching from proprietary systems or Elasticsearch itself, there might be a learning curve as they adapt to any differences or nuances.
  • Forking Concerns
    As a fork of Elasticsearch and Kibana, some users may have concerns about long-term feature parity or divergence from the systems they are used to.

ElasticSearch videos

What is Elasticsearch?

More videos:

  • Review - Real world Elasticsearch Compose/Stack File Review
  • Demo - Elastic Search

OpenSearch videos

OpenSearch - What the Fork is it?

Category Popularity

0-100% (relative to ElasticSearch and OpenSearch)
Custom Search Engine
83 83%
17% 17
Custom Search
86 86%
14% 14
Search Engine
81 81%
19% 19
Search API
90 90%
10% 10

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare ElasticSearch and OpenSearch

ElasticSearch Reviews

Log analysis: Elasticsearch vs Apache Doris
Benchmark tests with ES Rally, the official testing tool for Elasticsearch, showed that Apache Doris was around 5 times as fast as Elasticsearch in data writing, 2.3 times as fast in queries, and it consumed only 1/5 of the storage space that Elasticsearch used. On the test dataset of HTTP logs, it achieved a writing speed of 550 MB/s and a compression ratio of 10:1.
4 Leading Enterprise Search Software to Look For in 2022
“ We’ve built some big data search and mobile desktop applications that help our customers experience fast natural language search. Some applications require this, where I need to find data, I don’t want to build some complex query, I just need to ask the system “help me search for this information, narrow my results” and I don't want to wait several seconds. We’ve built a...
Top 10 Site Search Software Tools & Plugins for 2022
Elasticsearch is built for human users, which means that it’s equipped to handle mistakes that humans often make such as typos. This helps to improve search relevance and enhance the overall search experience. It offers real-time crawling, which automatically detects changes in content and ensures that search results are fresh and relevant.
Best Elasticsearch alternatives for search
However, when it comes to dealing with synonyms (i.e. ‘smart phone’ for ‘Samsung Galaxy’), slang (i.e. ‘kicks’ for ‘Nike Air Jordans’) and context (i.e. ‘car park’ is different to ‘dog park’) – you have to set up a bunch of manual rules/definitions with Elasticsearch and co.
Source: relevance.ai
5 Open-Source Search Engines For your Website
Elasticsearch provides key features like Advanced Full-Text Search Capabilities like Data indexing, Search capabilities including phrases, wildcards, auto suggestions, filters & facets, etc... Elasticsearch can also be used for other use-cases like
Source: vishnuch.tech

OpenSearch Reviews

We have no reviews of OpenSearch yet.
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Social recommendations and mentions

Based on our record, OpenSearch should be more popular than ElasticSearch. It has been mentiond 26 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

ElasticSearch mentions (17)

  • ElasticSearch from the Azure store or from Elastic.co?
    What surprised me is that on the Azure store, the only option I see is (Pay as you go), whereas on elastic.co there are the standard platinum and enterprise tiers followed by a where to deploy page and a pricing overview. Source: almost 2 years ago
  • Hunspell on elastic.co cloud
    Can anyone help me how to upload custom hunspell stemmer files to elastic cloud (elastic.co)? According to elastic docs it should go under elasticsearch/config/hunspell, but according to cloud docs I should upload it via features/extension tab. So I tried zipping the hunspell folder and uploading it. I also figured out that it should be in the dictionaries folder, but after uploading it still doesn't work. Source: almost 2 years ago
  • Creating a modern, SaaS website.. what am I missing?
    I can't figure out where I have to go to get more or less of a custom, premium website. I should mention that I look up to websites like elastic.co for example, would be very happy with something like that. I could really use some guidance! Source: about 2 years ago
  • Ask HN: Who is hiring? (October 2022)
    Elastic | Multiple software engineering roles | REMOTE (EMEA) | Full-time | https://elastic.co Elastic offers solutions for security and observability that are built on a single, open technology stack that can be deployed anywhere. Elastic Security enables security teams to prevent, detect, and respond to attacks with a solution built atop the speed and reliable of the Elastic stack. The Security External... - Source: Hacker News / over 2 years ago
  • Seeking clarification about which part of ElasticSearch to use for our website
    I have been trying to digest the elastic.co website to try to understand how we can use elastic search, but I've come to a point where I'm not sure which part of elastic, (if any) makes sense for us. In fact I am royally confused. I wonder if anyone here can help clarify? Source: almost 3 years ago
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OpenSearch mentions (26)

  • Why You Shouldn’t Invest In Vector Databases?
    In fact, even in the absence of these commercial databases, users can effortlessly install PostgreSQL and leverage its built-in pgvector functionality for vector search. PostgreSQL stands as the benchmark in the realm of open-source databases, offering comprehensive support across various domains of database management. It excels in transaction processing (e.g., CockroachDB), online analytics (e.g., DuckDB),... - Source: dev.to / 13 days ago
  • 🦿🛴Smarcity garbage reporting automation w/ ollama
    Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / over 1 year ago
  • Tutorial: Modifying Grafana's Source Code
    As you can see the visualisation performs rather well with InfluxDB except for one button which appears to be disabled:** Logs for this span**. This button is automatically disabled when our trace data source (in this case, Jaeger with InfluxDB 3.0 acting as the gRPC storage engine) has not been configured with a log data source. A log data source within Grafana is usually represented by default using the log... - Source: dev.to / over 1 year ago
  • WebArena: A Realistic Web Environment for Building Autonomous Agents
    Interesting work with the representation of the Content through the URL, to allow the agent/actor to discover the information through different path. ↓ [...] - CSS(--variable) - DOM(attributes=value) - FORM(input[name]) - URL(path?param#resource) - HTTP(?params{body}) - SCRIPT(--attribute) - DB(model?filters) - FS(folder/filer/{content}) [...] ↑ - https://www.w3.org/OWL/ maybe to harmonize the... - Source: Hacker News / almost 2 years ago
  • Ingesting Data into OpenSearch using Apache Kafka and Go
    Scalable data ingestion is a key aspect for a large-scale distributed search and analytics engine like OpenSearch. One of the ways to build a real-time data ingestion pipeline is to use Apache Kafka. It's an open-source event streaming platform used to handle high data volume (and velocity) and integrates with a variety of sources including relational and NoSQL databases. For example, one of the canonical use... - Source: dev.to / almost 2 years ago
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What are some alternatives?

When comparing ElasticSearch and OpenSearch, you can also consider the following products

Algolia - Algolia's Search API makes it easy to deliver a great search experience in your apps & websites. Algolia Search provides hosted full-text, numerical, faceted and geolocalized search.

Typesense - Typo tolerant, delightfully simple, open source search 🔍

Apache Solr - Solr is an open source enterprise search server based on Lucene search library, with XML/HTTP and...

Site Search 360 - Site Search 360 enhances and improves your built-in CMS or product search with autocompletion, semantic search, filters, facets, detailed analytics, and a whole lot of customization options.

Meilisearch - Ultra relevant, instant, and typo-tolerant full-text search API

Sphinx Search - Sphinx is an open source full text search server, designed with performance, relevance (search quality), and integration simplicity in mind. Sphinx lets you either batch index and search data stored in files, an SQL database, NoSQL storage.