Azure Cognitive Search

 

This article is a continuation of the series of articles starting with the description of SignalR service. In this article, we begin to discuss Azure cognitive search service aka Azure Search, after the last article on Azure Stream Analytics.   

Azure Cognitive Search differs from the Do-It-Yourself techniques in that it is a fully managed search-as-a-service, but it is primarily a full-text search. It provides rich user experience with searching all types of content including vision, language and speech. It provides machine learning features to contextually rank search results. It is powered by deep learning models. It can extract and enrich content using AI-powered algorithms. Different content can be consolidated to build a single index. 

The search service supports primarily indexing and querying. Indexing is associated with the input data path to the search service. It processes the content and converts them to JSON documents. If the content includes mixed files, searchable text can be extracted from the files. Heterogeneous content can be consolidated into a private user-defined search index. Large amounts of data stored in external repositories including Blob storage, Cosmos DB or other storage can now be indexed.  The index can be protected against data loss, corruption and disasters via the same mechanisms that are used for the content.  Index is also independent from the service so if one goes down, another can read the same service.  

The querying service supports search experience from a variety of clients and occurs on the outbound path of the search service. The index and the querying service are separate. In this article, we will compare this service with other search services. 

The Microsoft Search differs from this Azure Search service in that it searches Sharepoint. It enables users who are authenticated by Microsoft 365 and need to query over content in Sharepoint. The content flows into the libraries via connectors. Cognitive Search service, on the other hand, searches an index that the user determines and specifies what content must be indexed. The indexing pipeline can be enhanced with machine learning and text analysis. This service is also positioned as a plugin for a variety of applications.

Bing Search API maintains an index for the internet using web crawlers. There is an option for custom search where the same technology for different content types can be scoped to individual web sites. Cognitive search is geared for content from Azure data sources. It can index any json document that conforms to its service across clients and data sources.

The Database search technology is an offering from database platforms that provide a builtin search capability for the content stored in their databases. There is probably the most overlap between data that can be indexed in this case. Both database platforms and cognitive search can index this data very well but the latter provides advanced features for deep learning. If search and storage must be combined, SQL Server and CosmosDB have out-of-box features to support this use case. Many solutions use both but only Cognitive service can perform advance text and natural language processing with its features for autocorrection of misspelled words, synonyms, suggestions, scoring controls, facets and custom tokenization. The Azure cognitive search persists data only in the form of an inverted index and it provides no solution for data storage. The use case where a data storage might be required to be independent from the search service could include the case where the database is targeted towards the online transaction processing and the cloud service is externalized to adjust elastically to query volume.

 

If a dedicated search functionality is desired, on-premise solutions and cloud service can be compared.  The cloud service provides a turn-key and one-stop-shop solution for search. The on-premise solutions provider greater flexibility for controls over indexing, querying and results filtering syntax. There might be specialized solutions that span the cloud but they are meant for advanced users and still might not match the experience from Azure Search Service.

These are some of the advantages of using the Azure Search Service.