Azure Search is a recent addition to Microsoft's Infrastructure as a Service (IaaS) approach.

In 2008 Microsoft released the Azure platform with a cloud based component code-named project Red Dog.

[1] The years leading up to 2013 were spent developing the Azure framework within the scope of a Microsoft environment.

Azure Search provides two different indexing engines: Microsofts own proprietary natural language processing technology or Apache Lucene analyzers.

Lucene query syntax provides features similar to simple query syntax for logical operators and wildcard searches while also supporting more complicated functions such as proximity search and fuzzy search, Pre-built AI powered enrichments (known as cognitive skills) can be used to extract text from images, blobs, and other unstructured data sources.

Developers can also create custom skills and apply them to the AI enrichment pipeline.

The main purpose of AI enrichments is to extract structure out of unstructured information in order to make it searchable.

Users can drill down or filter search results by using criteria such as categories, prices and brand.