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For administrators, Magnolia provides a transparent, preconfigured search indexing configuration where you define what content is indexed and how it is weighted. By default Magnolia search functionality is provided by Apache's Jackrabbit search. For high asset volumes (100,000+ DAM assets) and advanced search requirements you can configure Magnolia to use Apache Solr instead.

The Magnolia Travels demo includes a complete search example, including how to search for content that is stored in a content app. For front-end developers, Magnolia provides search templating functions to render search results using only a template script.

Jackrabbit search

Apache's Jackrabbit search implementation meets the requirements of JSR 170 and supports some advanced proprietary features such as:

  • Extracting text from binary content.

  • Text excerpts with highlighted words matching the query.

  • Searching for a term and its synonyms.

  • Search for similar nodes.

  • Defining index aggregates.

Jackrabbit uses Lucene, a high-performance, full-featured text search engine library written in Java.

For more information about configuring Magnolia's Jackrabbit implementation, see the Jackrabbit search page.

Solr search

Apache Solr is an open source enterprise search platform with a REST-like API. Its major features include:

  • Dynamic clustering.
  • Hit highlighting.
  • Database integration.
  • NoSQL features.
  • Rich document handling.

Solr also uses Lucene for full-text indexing.

For more information about installing and configuring the Solr implementation, see the Solr search page.

See also