Who is the Company

A global healthcare and services company with over $3B in net revenue.

The Challenge

The company was using Adobe Experience Manager, an all-inclusive content management platform that combines everything needed to manage a website. The company was dependent on the out of the box AEM site search technology based upon the Apache Lucene project. Unfortunately, this built-in component suffered from several limitations, including:

  • Degraded search performance after 10,000 pages
  • Severe increase in the repository size since Lucene search took a lot of space to index binaries
  • Putting more effort into surfacing content from search results than with other contemporary search platforms

In brief, the company wanted:

  • A scalable, high-performance search capability: The company had a high content volume explaining how their devices help treat various chronic health conditions. The high volume caused website search performance to steadily decline. They wanted a search solution that would easily scale and maintain high performance.
  • A cost-effective alternative to the current system: Their existing search engine used a tremendous amount of storage while creating indexes, skyrocketing cloud storage costs.
  • A modern customer search experience: Their customers were demanding better search features. To meet the demands, they needed a platform with modern search features like smart sorting, natural language support, query elevation, intelligent suggestions, etc.

The Solution

Our CMS team migrated the native Lucene-based search to Apache Solr to improve the company’s search capabilities. It resulted in enhanced functionality and performance without additional software licensing costs.

The Solr search component handles all end-user requests. The Solr environment is configured to interact with AEM via a Java service created by our team. The Java service includes an Apache Sling model incorporated into a Java OSGI module. A Java Content Repository (JCR) query extracts information from the AEM content repository. The results are then indexed and filtered before being passed back to the end user.


Here are some highlights of our solution:

  • 8x increase in search response: The primary benefit for the company after our team integrated Solr search is increased performance. Site search response time went from 17 seconds down to less than two seconds!
  • Highly scalable: The Apache Solr solution easily scales to meet high volume demand without impacting overall system performance and avoids the heavy resource usage of the company’s existing search architecture.

Business Impact

  • Vastly improved customer search experience increases customer satisfaction: The new system handles advanced features like full-text search, highlighted results, synonym search, similar keyword suggestions, natural language, and multi-language support with ease.
  • Fast and accurate search response improves sales: Since customers now receive precise search results rapidly, they are more inclined to pursue a search for additional products.
  • Lower cloud costs: Our solution requires fewer cloud resources, reducing a huge amount of cloud usage fee. The old system used quite a bit of space to create its indexes that expanded the repository size. The new system requires less space, reducing storage costs.

Technologies Used

Adobe Experience Manager: Cloud-based all-inclusive omnichannel content management platform
Apache Solr: Open-source Java-based enterprise search platform
Apache Sling: OSGI compliant open-source framework for REST services
Apache Lucene: Widely used open-source search engine
OSGI: Standards-based dynamic module system for Java

Related Capabilities

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