Opensearch vs Elasticsearch – AWS and Elastic Forks Compared

Just like two siblings who graduate from the same school and embark on different career paths, OpenSearch and Elasticsearch share a common root but have evolved uniquely. Both powerful search engines have their origin in the same codebase, yet they’ve taken divergent paths in the tech world.

OpenSearch is essentially a fork from Elasticsearch. In the tech realm, a fork signifies a divergence where developers take the source code of one software, start independent development on it, and create a distinct entity. OpenSearch began its journey as Elasticsearch, but developers decided to steer it towards a new trajectory.

In this article, we’ll provide an in-depth comparison of OpenSearch and Elasticsearch. We’ll explore a variety of parameters, including security measures, licensing, core features, community support, and more. By the end of this discussion, you’ll have a clearer understanding of these two search engines and be better positioned to choose between them. So, let’s dive into the fascinating world of OpenSearch and Elasticsearch!

TL;DR: What are the main differences between OpenSearch and Elasticsearch?

OpenSearch and Elasticsearch are both powerful search engines derived from the same codebase. OpenSearch is a fork from Elasticsearch and is completely free, offering a full suite of security features and community-driven support. Elasticsearch, on the other hand, reserves some of its advanced features for its premium version. The choice between the two will depend on your specific needs, budget, and preference for community support versus premium support. Read on for a more detailed comparison.

Security Measures: A Crucial Consideration

In the realm of data management, security takes center stage. It’s akin to the lock and key mechanism of a vault, controlling who gets access to what. Both Elasticsearch and OpenSearch acknowledge this importance and offer features that enable administrators to regulate data access. But how do they stack up against each other?

Elasticsearch, in its free version, offers basic security features akin to a standard lock, such as password protection and encryption. However, to access more advanced features like role-based access control, field and document level security, and audit logging, akin to a high-tech security system, you need to upgrade to the premium version.

Conversely, OpenSearch, being completely free, offers a full suite of security features right off the bat. This includes role-based access control, multi-tenancy, audit logging, and encryption, among others.

These security features carry significant implications for businesses. They not only safeguard sensitive data but also ensure that only authorized personnel can access specific data. This is especially crucial for businesses handling sensitive customer information or proprietary data. The right security measures can help avert data breaches, uphold customer trust, and comply with data protection regulations.

Thus, when choosing between Elasticsearch and OpenSearch, the decision could very well pivot on the security features. If your business requires advanced security features but is on a tight budget, OpenSearch might be the more appealing option. However, if budget is not a constraint and you prefer a more established platform, Elasticsearch’s premium version could be your go-to.

Licensing and Support:

Choosing a search engine for your enterprise is not just about the features, it’s also about the license type and the support options available. Let’s delve deeper into how Elasticsearch and OpenSearch stack up against each other in these aspects.

In terms of emergency support, Elasticsearch offers a variety of options, akin to a multi-tool kit. These include online forums, documentation, and premium support with guaranteed response times for critical issues. However, this premium support comes at a price, which might pose a hurdle for smaller businesses or startups.

Contrastingly, OpenSearch, being a community-driven project, is like a neighborhood tool-sharing program. It relies on community support through forums and GitHub. While this might not guarantee immediate response times, it fosters a collaborative environment where users can assist each other in problem-solving.

Shifting our focus to licensing, Elasticsearch was initially released under the open-source Apache 2.0 license. However, recent versions have transitioned to a Server Side Public License (SSPL), which is not recognized as an open-source license by the Open Source Initiative (OSI). This shift has implications for product development, as it restricts how you can use the software in a service offering.

On the other hand, OpenSearch continues under the Apache 2.0 license, ensuring that it remains completely open source and free to use, modify, and distribute. This implies fewer restrictions on how you can use the software, making it a more flexible option for product development.

These license restrictions can also carry potential legal implications. For instance, using Elasticsearch under SSPL in a service offering without adhering to the license terms could invite legal action. Conversely, the Apache 2.0 license of OpenSearch offers more freedom, reducing the risk of legal complications.

In conclusion, the choice of license can significantly impact the long-term viability of a product. If your business model involves offering a service based on the search engine, OpenSearch’s Apache 2.0 license offers more flexibility and fewer legal risks. However, if you require guaranteed support response times and are willing to pay for it, Elasticsearch’s premium support might be worth considering.

Core Features and Documentation: Delving Deeper

Choosing between OpenSearch and Elasticsearch is akin to selecting a car. The unique features each offers and the quality of their respective user manuals (documentation) are pivotal factors to consider. Let’s dive deeper into these aspects.

Unique Features

Both OpenSearch and Elasticsearch come packed with a rich set of features, making them the Ferraris and Lamborghinis of search engines. Elasticsearch, being the older of the two, offers a more extensive set of features. These include full-text search, distributed search, and multi-tenancy. It also boasts a robust analytics engine, enabling users to perform complex data analysis.

OpenSearch, while offering many of the same features as Elasticsearch, also introduces some unique offerings to the table. One of these is its Trace Analytics feature, which allows users to analyze trace data from distributed applications. This can be particularly beneficial for troubleshooting and performance optimization.

Documentation and Community Support

When it comes to user manuals (documentation), both Elasticsearch and OpenSearch provide comprehensive guides and resources. Elasticsearch, being more established, has extensive documentation that covers almost every aspect of the software. However, being a premium product, some of the more advanced features are only covered in the paid documentation.

OpenSearch, on the other hand, has made significant strides in developing its documentation since its fork from Elasticsearch. The community plays a significant role in this, filling in gaps and continually updating the documentation. While it might not be as extensive as Elasticsearch’s, the OpenSearch documentation is completely free and covers all the features of the software.

Comprehensive documentation is crucial for user adoption and learning. It not only helps users get started with the software but also serves as a reference for troubleshooting and optimizing usage. Therefore, the availability and quality of documentation can significantly influence the choice between OpenSearch and Elasticsearch.

The choice between OpenSearch and Elasticsearch can hinge on the unique features each offers and the quality of their documentation. If Trace Analytics and a completely free, community-driven documentation appeal to you, OpenSearch might be the way to go. However, if you prefer a more established platform with a wider range of features and comprehensive, albeit partially paid, documentation, Elasticsearch could be the better choice.

Community Engagement and Dashboards:

The strength of a product is often reflected in its community. Imagine a bustling marketplace where everyone contributes to the growth, offers support, shares knowledge, and helps shape its future. That’s the essence of a vibrant community in the tech world. So, how do Elasticsearch and OpenSearch measure up in terms of community engagement and contributions?

Elasticsearch, having been around for a longer time, boasts a large and active community. This community is like a bustling marketplace, contributing to the product’s development, providing support through forums, and adding plugins and extensions. However, the recent shift in Elasticsearch’s licensing has stirred some concern in the community, leading to a slowdown in contributions.

OpenSearch, being a newer entrant, is still nurturing its community. However, the project has witnessed significant community engagement since its inception, with contributions pouring in from developers worldwide. The community actively participates in shaping OpenSearch’s future, contributing to its codebase, documentation, and plugins.

Dashboard Features

When it comes to dashboards, both Elasticsearch and OpenSearch offer powerful visualization tools, akin to a painter’s palette. Elasticsearch comes with Kibana, a robust visualization tool that allows users to create interactive dashboards. Kibana offers a wide spectrum of visualization options, including charts, graphs, maps, and more.

OpenSearch, on the other hand, offers OpenSearch Dashboards, a fork of Kibana. OpenSearch Dashboards retains many of Kibana’s features but is being developed independently, with new features being added based on community feedback.

Future Directions

The future trajectory of OpenSearch Dashboards looks promising, with plans for enhanced visualization capabilities, better integration with other OpenSearch features, and more user-friendly interfaces. The community is actively involved in shaping these developments, contributing ideas and feedback to the project.

In conclusion, the level of community engagement can significantly influence the evolution and adoption of a search engine. A vibrant community not only contributes to the product’s development but also provides a support network for users.

So, if you value a dynamic, active community and a product that is shaped by its users, OpenSearch might be your ideal choice. However, if you prefer a more established product with a large user base and a wide array of plugins and extensions, Elasticsearch could be a better fit.

Additional Tools, Plugins, and Support Services:

Beyond the fundamental features and licensing, additional tools, plugins, and support services are like the accessories and after-sales service of a car. They play a vital role in enhancing the functionality of a database and providing users with the necessary support. Let’s see how Elasticsearch and OpenSearch fare in these aspects.

Log Collection and Aggregation Tools

Both Elasticsearch and OpenSearch are compatible with a variety of log collection and aggregation tools, akin to different types of car diagnostic tools. These tools collect logs from various sources, aggregate them, and send them to the database for indexing and analysis.

Some popular tools compatible with both databases include Logstash, Fluentd, and Beats for Elasticsearch, and Data Prepper for OpenSearch.

Plugins

Plugins act as the add-ons that significantly enhance the functionality of a database, allowing users to add features and capabilities based on their specific needs.

Elasticsearch offers a wide range of plugins, including those for security, alerting, machine learning, and more. However, some of these plugins are only available in the premium version, much like certain car accessories are only available with the high-end model.

OpenSearch, on the other hand, comes with all the plugins that were available in the open-source version of Elasticsearch, and more are being added by the community. These plugins are completely free and cover a range of functionalities, including security, alerting, index management, and more.

Support Services

When it comes to support services, both Elasticsearch and OpenSearch offer a range of options. Elasticsearch provides online forums, documentation, and premium support with guaranteed response times. OpenSearch, being a community-driven project, relies on community support through forums and GitHub. While this might not guarantee immediate response times, it fosters a collaborative environment where users can help each other solve problems, much like a community of car enthusiasts.

The availability of additional tools, plugins, and support services can significantly influence the choice between Elasticsearch and OpenSearch. If you value a wide range of free plugins and a collaborative support environment, OpenSearch might be the right choice for you. However, if you prefer a more established product with a larger selection of plugins and guaranteed support response times, Elasticsearch could be a better fit.

Summary: OpenSearch vs Elasticsearch – The Final Showdown

Choosing between OpenSearch and Elasticsearch is like deciding between two cars, each with its own unique strengths and features. Both are powerful search engines, akin to high-performance vehicles, each with its own unique strengths and weaknesses.

When it comes to security measures, OpenSearch offers a full suite of features for free, much like a car with all the safety features included in the base model. Elasticsearch, on the other hand, reserves some of its more advanced safety features for its premium version.

In terms of licensing and support, Elasticsearch offers premium support with guaranteed response times, akin to a car manufacturer offering premium after-sales service. However, its shift to a Server Side Public License has raised eyebrows, much like a car manufacturer changing its warranty terms. OpenSearch, on the other hand, remains under the Apache 2.0 license and relies on community support, much like a community of car enthusiasts helping each other out.

In terms of unique features and documentation, Elasticsearch offers a more extensive set of features and comprehensive documentation, though some of it is paid. OpenSearch, while still developing its user manual (documentation), offers unique features like Trace Analytics.

Community engagement is strong in both, with Elasticsearch having a larger user base and OpenSearch fostering a collaborative environment. Both offer powerful dashboard features, much like the sophisticated infotainment systems found in modern cars, with Kibana for Elasticsearch and OpenSearch Dashboards for OpenSearch.

Finally, both are compatible with a variety of log collection and aggregation tools and offer a range of plugins and support services. However, OpenSearch offers all its plugins for free, much like a car that comes with all accessories included in the base model, while Elasticsearch reserves some for its premium version.

Conclusion

The choice between OpenSearch and Elasticsearch depends on your specific needs, budget, and preference for community support versus premium support. Both are powerful tools, and your choice will ultimately depend on which strengths align best with your needs. Just like choosing a car, the decision should be based on which one aligns best with your requirements and preferences.