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Constructing a robust search engine functionality for your application or website is crucial to achieving effective monitoring and analysis. When discussing the best and most appropriate open-source search engines, two particularly popular solutions arise, OpenSearch and Solr. These solutions are very similar, offering the majority of the same features, capabilities, and use cases. However, there are differences between the two search engines that make them better tailored for particular scenarios. So, to assist you in selecting the most appropriate search engine for your organization, in this article, we will outline the key similarities and differences between OpenSearch and Solr.
What is Solr?
Apache Solr is an open-source enterprise search platform built on Apache Lucene, providing extensive indexing and search capabilities for a broad variety of use cases. With Solr, users can index and search structured and unstructured data, including text, documents, images, and rich media, enabling fast and accurate retrieval of relevant information. Also, Solr supports advanced search features such as full-text search, faceted search, highlighting, spell-checking, and geospatial search, offering a comprehensive solution for building search applications.
What is OpenSearch?
OpenSearch is a powerful and open-source distributed search and analytics engine, built on Apache Lucene, designed to deliver scalable, real-time search and analytics capabilities. It allows organizations to index, search, and examine large volumes of data efficiently, catering to diverse use cases such as log analytics, monitoring, and business intelligence. The solution provides RESTful APIs for simple integration with other systems, along with a plugin architecture for extending its functionality.
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OpenSearch vs Solr
It’s important to note that when determining which search engine is best for your organization, we recommend selecting the solution that you and your team are most familiar with and comfortable with due to how similar these tools are. But as both of these tools are widely used it’s likely that your team will be familiar with both of the solutions. So, to help you decipher the best search engine for your organization and use case we will outline some similarities and differences between OpenSearch and Solr.
| Similarities | OpenSearch and Solr |
|---|---|
| Search Capabilities | Both OpenSearch and Solr offer extensive search capabilities, including full-text search, faceted search, highlighting, spell-checking, and geospatial search. They allow you to index and search diverse data types, such as text, documents, images, and rich media, with fast and accurate retrieval of relevant information. |
| Scalability | Both platforms are designed to be scalable, enabling you to implement clusters with multiple nodes to manage large volumes of data and query traffic. They support distributed indexing and search, replication, and failover mechanisms to guarantee uninterrupted service and high availability. |
| Flexibility | OpenSearch and Solr offer flexibility in terms of data sources, integration, and customization. They offer RESTful APIs, client libraries, and connectors for seamless integration with multiple data sources, platforms, and programming languages. Users can customize and extend their functionality through plugin architectures and customization options. |
| Differences | OpenSearch | Solr |
|---|---|---|
| Development & Governance | OpenSearch is an open-source project developed and governed by a community of contributors, initially as a fork of Elasticsearch. | Solr is an Apache Software Foundation project with a long-standing history and strong community support. |
| Ecosystem | OpenSearch, being a newer project, is still growing its ecosystem but benefits from compatibility with existing Elasticsearch plugins and integrations. | Solr has a mature and extensive ecosystem with a wide range of plugins, extensions, and integrations available. It has been adopted by many organizations and has a large community of users and contributors. |
| Architecture | OpenSearch uses a distributed architecture with built-in clustering and node coordination for indexing and search operations. | Solr uses a traditional master-slave architecture, where a single node (master) coordinates indexing and search operations, while multiple nodes (slaves) store the indexed data. |
| Documentation & Support | OpenSearch, being a newer project, is still building its documentation and community support resources, although it benefits from compatibility with existing Elasticsearch documentation and community forums. | Solr has extensive documentation, tutorials, and community support resources available, reflecting its maturity and widespread adoption. |
OpenSearch vs Solr: Use Cases
When deciding between OpenSearch and Solr as a search engine, it’s important that you take into account your organization and use case.
Log Analytics
For log analytics use cases, both OpenSearch and Solr offer powerful full-text search capabilities, making it simple to index and search log data efficiently. They support features like faceted search, highlighting, and aggregation, enabling you to attain insights into log data. Both platforms are highly scalable and can manage large volumes of log data, making them suitable for high-throughput log ingestion and analysis. However, OpenSearch may have a slight advantage in this use case due to its real-time analytics capabilities and integration with other AWS services like Amazon CloudWatch Logs for seamless log ingestion and monitoring.
E-commerce Search
In e-commerce search applications, both OpenSearch and Solr excel in offering quick and accurate search results for product catalogs. They support features like faceted search, spell checking, and relevancy tuning, allowing you to refine search results and discover products effectively. Both platforms are highly customizable, enabling you to tailor search results based on business requirements and user preferences. However, Solr's vast ecosystem and mature feature set may give it an edge in this use case, offering a broad variety of plugins, extensions, and integrations for building advanced e-commerce search solutions.
Enterprise Search
For enterprise search use cases, both OpenSearch and Solr provide robust search capabilities for indexing and searching internal documents, websites, and knowledge bases. With features such as documented highlighting, faceted search, and security integration, you’re able to locate relevant information quickly and securely. Both platforms are highly scalable and can manage large document repositories, making them suitable for enterprise-scale deployments. However, Solr's mature ecosystem and extensive documentation may make it a more popular choice for enterprise search applications, offering extensive support and resources for building and managing search solutions.
Geospatial Search
In geospatial search applications, both OpenSearch and Solr offer advanced capabilities for searching and analyzing spatial data. Supporting features include geographic indexing, distance queries, and spatial filtering, enabling you to conduct complex geospatial queries with ease. Both platforms can manage large geospatial datasets and offer high-performance search and analytics capabilities. However, Solr's mature ecosystem and specialized plugins for geospatial analysis can give it an advantage in this use case, offering additional functionality and integration options for building geospatial search applications.
Hosted OpenSearch
From reading our comparison guide you may have decided that OpenSearch is the most appropriate search engine for your organization. If so, the configuration and maintenance of this tool can be daunting. However, you can alleviate this concern with Logit.io’s hosted OpenSearch solution. With hosted OpenSearch, you entrust us to host and maintain your OpenSearch Stacks. This allows you to gain from the added value offered by using a single platform for data centralization. Logit.io also provides everything you need to launch legacy ELK Stacks as well as Grafana data visualizations. If you’re interested in finding out more about hosted OpenSearch from Logit.io, don’t hesitate to arrange a free demo or begin using the platform for yourself with a 14-day free trial.
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