What is federated search?

Laurent Cazanove -

Searching across disparate data sources can be a real headache. But aggregating information from various databases or indices enables the creation of more relevant search experiences for users. In this guide, we'll explore what federated search is and the use cases it unlocks.

Federated search empowers you to conduct searches across multiple systems simultaneously. In the context of a search engine, federated search allows querying numerous indices and retrieving the results in a single, consolidated list.

This differs from having a monolithic index that stores various types of resources where documents could be filtered by type. Leveraging multiple indices enables the implementation of specific ranking rules for each index.

Federated search extends the capabilities of multi-index search, merging results into a unified, cohesive response. This allows surfacing the most relevant results across the entire dataset, rather than just the top hits for each individual index.

Federated search is a crucial feature for SaaS applications, where users frequently need to search through all available resources regardless of type. An example you might be familiar with is searching in Slack—a single search bar to find users, messages, and shared documents.

Integrating federated search into your application can facilitate more convenient search experiences. By supporting searches across multiple sources, you can build one search bar to query all the data. This eliminates the need for multiple menus or lists of results, resulting in a more intuitive and user-friendly interface.

The search experience is further enhanced by the increased relevance of the results. The comprehensiveness of the returned resources will match items that the user may not have initially considered including in their search (e.g., discovering a prospect's email in meeting notes instead of just contact details).

Uncovering the most pertinent result can be transformative for your users and your business. In an internal tool, relevant results enable users to make more informed decisions. However, in customer-facing applications, it can be the pivotal factor between converting a sale or not.

Locating information effortlessly within your application or e-commerce platform leads to higher customer satisfaction and improved retention. This allows users to extract more value from the service, ultimately elevating the overall experience quality.

How federated search improves developer experience

Implementing federated search leads to a more streamlined search implementation process. With federated search, results are delivered in a single, unified list, simplifying front-end development. This goes beyond multi-index search because it comes without the added complexity of implementing front-end logic to merge, sort, and paginate the results.

In this setup, the relevance of documents can be further fine-tuned thanks to granular, per-index configuration. This allows tailoring the relevancy settings to specific data types (a specific index) rather than the entire dataset (all indices). As a federated search request comes, the search engine can ensure that the most important results rise to the top.

This also simplifies extending the search functionality if new types of documents need to be included in the future. You'll only need to focus on configuring the relevancy settings for the new document type, instead of revisiting the relevancy for the entire dataset.

Conclusion

Federated search enables performing searches against multiple indices of a search engine and returns a single, consolidated list of results. With a search engine that supports federated search, developers can build more relevant user search experiences without incurring additional complexity.

Federated search is available in Meilisearch 1.10 and higher. Learn more about implementing federated search with Meilisearch by reading the documentation. Check out which search engines support federated search and other key features via our comparison of search engines.

Meilisearch is an open-source AI-powered search engine enabling developers to build state-of-the-art experiences while enjoying simple, intuitive DX.

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