In the world of search and analytics, Elasticsearch has long been a dominant player, offering a powerful and versatile engine for indexing, searching, and analyzing data. However, the landscape of search engines has evolved, and a fork of Elasticsearch called OpenSearch has emerged as a compelling alternative. The question that often arises is: which one is better to use for your specific needs? In this comprehensive comparison, we will explore the features, community support, licensing, governance, ethics, and principles of OpenSearch and Elasticsearch to help you make an informed decision. Get OpenSearch and Elasticsearch support services by Nextbrick, Inc before making your selection.
OpenSearch and Elasticsearch Features:
Both OpenSearch and Elasticsearch are renowned for their rich set of features, making them suitable for a wide range of use cases. To understand their capabilities, let’s break down the features into categories: common, competing, and diverging.
Common Functionality:
Both engines share a common foundation in Lucene, the open-source search library. This means that essential functionalities such as document indexing, merging, similarities, and filter caches are exposed in both Elasticsearch and OpenSearch. Furthermore, as both projects upgrade to newer versions of Lucene, they inherit the same improvements, bug fixes, and trade-offs.
Apart from Lucene, common functionality also arises from Elasticsearch 7.10.2, which served as the basis for OpenSearch. However, as these two engines evolve independently, more of this shared code will be replaced with parallel developments.
Competing Functionality:
The genesis of OpenSearch lies in addressing proprietary features in Elasticsearch. Competing functionality includes critical aspects like authentication, authorization, index management, and alerting, which were traditionally proprietary in Elasticsearch. OpenSearch provides open-source alternatives to these features, such as Index State Management in contrast to Elasticsearch’s Index Lifecycle Management. While they serve similar purposes, differences in implementation exist, and these details can change over time. Elasticsearch often appears more mature in this aspect.
However, it’s worth noting that not all Elasticsearch functionality is free, even though it falls under the Basic license. For instance, index lifecycle management is free, but cross-cluster replication is not, and you can find a comprehensive list of such features.
Diverging Functionality:
Both Elasticsearch and OpenSearch introduce unique features not replicated by the other. For instance, Elasticsearch offers Time Series Data Streams, while OpenSearch has reintroduced segment replication. Although these distinctions may seem minor currently, ongoing development in both projects will likely lead to more diverging functionalities.
Elasticsearch has a notable focus on log and time series use cases, while OpenSearch may gather more contributions for enterprise search due to the absence of free Elasticsearch counterparts in areas like machine learning.
Community
Community support plays a crucial role in the sustainability and growth of open-source projects. A thriving community ensures that the software remains relevant, receives timely updates, and benefits from diverse perspectives.
Elasticsearch Community:
Elasticsearch initially boasts a larger number of commits and contributors. However, this comparison can be misleading since Elasticsearch’s GitHub repository includes X-Pack and all its plugins, like SQL and machine learning. OpenSearch maintains separate repositories for these components.
While it’s challenging to compare forum posts directly, Elasticsearch’s single category for everything ELK-related can lead to a higher aggregate number. Even when adjusting for these factors, Elastic’s community appears larger.
OpenSearch Community:
OpenSearch, having inherited commits pre-fork, initially saw a drop in contributions but is gradually gaining momentum. The project’s multiple categories for discussions, such as OpenSearch vs. OpenSearch Dashboards, make it harder to compile numbers directly comparable to Elastic’s forums.
However, Google Trends data indicates that interest in Elasticsearch has been slowly declining, while OpenSearch is experiencing a gradual increase in interest. This trend suggests that the gap between the two communities may narrow over time.
License and Governance
The licensing model and governance structure of a search engine have significant implications for its use and future development.
OpenSearch Licensing:
OpenSearch adopts the Apache License, providing users with considerable freedom in using and modifying the software. This permissive license allows you to utilize OpenSearch as you see fit.
Elasticsearch Licensing:
Elasticsearch primarily uses the Elastic License, which introduces restrictions, especially concerning providing Elasticsearch’s functionality as a service to others. This distinction is essential for businesses considering offering search functionality to external clients.
Governance:
Both OpenSearch and Elasticsearch allow public contributions to their codebases, but they are governed by different entities. OpenSearch is stewarded by AWS, while Elasticsearch is overseen by Elastic, the company that created it. The choice between these two governance models may influence your decision.
OpenSearch’s Apache license and governance structure make it more appealing to outside contributors and may align better with certain organizational policies regarding software licenses.
Ethics and Principles
The evolution of Elasticsearch and OpenSearch has given rise to differing narratives, with varying opinions on the ethics and principles of the organizations behind these projects.
Elasticsearch and Elastic’s Perspective:
Some view Elastic as the advocate for open-source values, defending the Elasticsearch trademark against what they see as Amazon’s misuse. Elastic’s move to change the license for new Elasticsearch versions has been seen as a reaction to AWS’s actions.
AWS and OpenSearch’s Perspective:
On the other hand, AWS has been praised for forking Elasticsearch and continuing development after Elastic’s licensing changes. AWS’s OpenSearch aims to provide a fully open-source alternative, addressing concerns about Elasticsearch’s direction.
A more balanced perspective acknowledges that both companies have contributed positively to the open-source community while also acting in their interests, sometimes in ways that conflict with the community’s views.
SaaS Variants
In addition to self-hosting, both Elasticsearch and OpenSearch offer managed versions. These managed services come with their own sets of features and considerations:
Elastic Cloud:
Elastic Cloud is a hosted Elasticsearch solution available at different license levels, from Standard to Enterprise. It works on multiple cloud providers, not just AWS. Choosing Elastic Cloud can provide flexibility in terms of cloud providers.
AWS OpenSearch Service:
AWS OpenSearch Service combines OpenSearch with additional proprietary features. It is specifically designed for AWS, making it a suitable choice for organizations heavily invested in the AWS ecosystem.
The decision between a managed service and self-hosting depends on factors like control requirements and scalability costs.
Conclusion
In the quest to choose between OpenSearch and Elasticsearch, there is no one-size-fits-all answer. The decision depends on your unique use case, preferences, and considerations.
Elasticsearch remains a solid choice for organizations seeking a mature solution with a comprehensive feature set. It boasts a mature ecosystem and offers a wide range of functionalities for search, analytics, and visualization. However, be mindful of licensing restrictions for certain features.
OpenSearch excels in providing open-source alternatives for proprietary features found in Elasticsearch. It introduces advanced security analytics, OpenSearch Dashboards for data visualization, machine learning capabilities, and more. If you prioritize open-source solutions or require specific features provided by OpenSearch, it may be the better fit.
No matter which search engine you choose, whether it’s Elasticsearch or OpenSearch, making an informed decision is essential for the success of your project. As you navigate this decision-making process, consider seeking expert guidance and support from Nextbrick, a trusted partner in the world of search consulting. Nextbrick can provide valuable insights, assist with migration, and offer vendor-neutral advice to ensure your search and analytics solution aligns perfectly with your organization’s needs. Your journey to optimizing search and analytics begins with the right choice, and Nextbrick is here to guide you every step of the way.