Search Orchestration

Streamlining Information Access

Search Orchestration is a method for querying multiple search indices at once while providing a single search result to the user.

Consumer sites such as TripAdvisor and Kayak, have employed this method to simplify the process of consolidating search results from multiple search engines.  SmartHub provides the ability to incorporate Search Orchestration into your environment.

 

Orchestrated Search Example
Search Orchestration Explained

Situations where organizations should consider Search Orchestration include:

When Indexing Isn’t Feasible.

  • Web Search Engines: engines such as Google and Bing devote enormous resources to crawling and processing the World Wide Web. It is impractical for an organization to replicate this, so a Search Orchestration approach makes sense.
  • Subscription sources:  many important sources of commercial content are available only through subscription or other licensing. For example, sources such as Bloomberg, LinkedIn, or LexisNexis, and content aggregators such as Northern Light and Web of Science do not allow crawling which makes Federation a feasible alternative.
  • Social Media: indexing all of twitter is beyond the resources of most organizations. Pragmatically it can be better to include a service like Topsy (or twitter itself) in an Orchestrated Search.

When a Central Index Isn’t Compliant.

In some multinational organizations, for compliance purposes it can be necessary to have separate indices that follow the data residency and data sovereignty of the sources that they index. Search Orchestration will deliver consolidated results from these indices.

When Indexing May Not Be Effective. 

  • Enterprise File Sync and Share (EFSS):  Google Drive, OneDrive, Box, and DropBox tend to contain enormous amounts of content that is essentially private to one person, alongside essential shared information. Although it is technically feasible to crawl these, it may not be advisable due to both the amount and quality of information these sources may contain. 
  • Big archives:  Large email and file archives present similar issues as EFSS solutions. Symantec, Mimecast, and Exchange archives can contain billions of emails, the vast majority of which are never referenced. These systems also have capable embedded search, usually optimized for their specific formats.

Key Features:

  • 1
    Sends user queries to multiple search engines simultaneously and consolidates results.
  • 2
    Supports Elastic Cloud, Elasticsearch, Azure Search, Office 365, SharePoint 2013 and SharePoint 2016 search, as well as the ability to add additional backends through a well-defined development process.
  • 3
    Delivers a single, interleaved search result rather than multiple result sets so that the user experience is seamless.
  • 4
    Configuration enables rationalization of relevancy models from different engines and merging of refinement values.