Engines and content sources

Tool compatibility introduces the concepts of indices, engines, and content sources. Engines and content sources are abstractions introduced by Enterprise Search. Many Enterprise Search tools are designed to operate on these abstractions rather than Elasticsearch indices.

You can create engines from indices, and you can access the index that corresponds to an engine or content source. You can use a meta engine to search across multiple engines.

This document provides the following solutions for working with engines and content sources:

See the App Search documentation to create an App Search engine containing documents from an existing Elasticsearch index. Use the features of an engine and still have access to the index.

Example use case: You have ingested documents into an Elasticsearch index directly and now you want to build a search experience for it.

Example use case: You have a Workplace Search content source and want to use the App Search search API to query the content.

Learn about the specific features and field types supported by Elasticsearch index engines.

To create an App Search engine from a Workplace Search content source:

Example use case: You’ve ingested content using a Workplace Search connector. You want to build a search experience for this content with relevance tuning features in App Search.

Example use case: You want to build a search experience that searches content in Workplace Search content sources and App Search engines. Create an App Search engine and then combine multiple engines using a meta engine for a unified search experience.

Meta engines allow you to combine multiple engines into one searchable engine. Users can leverage all App Search features for these engines. See the App Search documentation to learn all about meta engines.

Example use case: Your organization might have multiple content sources, each with different search settings and read/write permissions, but you also need a company-wide search experience with distinct curations or relevance tunings.

Example use case: You’ve ingested content into Elasticsearch indices using the Elastic web crawler. You’ve also ingested content into Workplace Search content sources using various Workplace Search connectors. You can create a unified search experience across all this content by creating engines and a meta engine.

See the App Search documentation to learn how to create meta engines in the Kibana UI.

You can access the underlying Elasticsearch index for an App Search engine. To find the index follow these steps in the Kibana UI:

Use the tools of your choice to manage and search the index’s documents.

Example use case: You created an App Search engine from an Elasticsearch index, but you still want to be able to access the index directly.

Example use case: You are an App Search user, but your requirements have outgrown the out-of-the-box capabilities of App Search. You want to leverage the full power of Elasticsearch to build more customized search experiences.

You can access the underlying Elasticsearch index for a Workplace Search content source. To find the index follow these steps in the Kibana UI:

Use the tools of your choice to manage and search the index’s documents.

Example use case: You want to create an engine from a content source. Accessing the underlying Elasticsearch index is a required intermediate step.

Example use case: You want to use Elastic index tools to work with the documents in a content source.