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  4. Search As A Service
  5. Azure Cognitive Search vs Yext Search Experience Cloud

Azure Cognitive Search vs Yext Search Experience Cloud

OverviewComparisonAlternatives

Overview

Azure Cognitive Search
Azure Cognitive Search
Stacks39
Followers67
Votes1
Yext Search Experience Cloud
Yext Search Experience Cloud
Stacks8
Followers9
Votes0

Yext Search Experience Cloud vs Azure Cognitive Search: What are the differences?

Yext Search Experience Cloud: Deliver official answers wherever your customers are searching. Consumer search behavior is changing rapidly. Take back control of your facts online, and deliver official answers wherever your customers are searching; Azure Cognitive Search: AI-powered cloud search service for mobile and web app development. It is the only cloud search service with built-in AI capabilities that enrich all types of information to easily identify and explore relevant content at scale. Formerly known as Azure Search, it uses the same integrated Microsoft natural language stack that Bing and Office have used for more than a decade and AI services across vision, language and speech. Spend more time innovating and less time maintaining a complex cloud search solution.

Yext Search Experience Cloud and Azure Cognitive Search can be primarily classified as "Search as a Service" tools.

Some of the features offered by Yext Search Experience Cloud are:

  • Create your business’s Knowledge Graph
  • Answer questions on your website
  • Capture high-intent customer traffic

On the other hand, Azure Cognitive Search provides the following key features:

  • Start, maintain and scale with minimal investment
  • Create searchable content using integrated AI
  • Customise to meet goals and industry requirements

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Detailed Comparison

Azure Cognitive Search
Azure Cognitive Search
Yext Search Experience Cloud
Yext Search Experience Cloud

It is the only cloud search service with built-in AI capabilities that enrich all types of information to easily identify and explore relevant content at scale. Formerly known as Azure Search, it uses the same integrated Microsoft natural language stack that Bing and Office have used for more than a decade and AI services across vision, language and speech. Spend more time innovating and less time maintaining a complex cloud search solution.

Yext's Answers Platform collects and organizes content into a Knowledge Graph, then leverages a complementary set of products to deliver relevant, actionable answers wherever customers, employees, and partners look for information.

Start, maintain and scale with minimal investment;Create searchable content using integrated AI;Customise to meet goals and industry requirements
Organize your content with a next-generation CMS built for AI; Deliver answers across a network of 200+ integration partners; Publish answers with landing pages built for SEO and conversion; Manage crowdsourced answers about your products and services; Deliver direct answers across websites, apps, and workspaces; Unlock actionable insights on the performance of your answers
Statistics
Stacks
39
Stacks
8
Followers
67
Followers
9
Votes
1
Votes
0
Pros & Cons
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Integrations
Postman
Postman
Java
Java
Node.js
Node.js
Python
Python
C#
C#
PowerShell
PowerShell
Dasheroo
Dasheroo
Movable Ink
Movable Ink
Adobe Experience Manager
Adobe Experience Manager
Hootsuite
Hootsuite
Tableau
Tableau
Shopify
Shopify
HubSpot
HubSpot
WordPress
WordPress
Zapier
Zapier
Magento
Magento

What are some alternatives to Azure Cognitive Search, Yext Search Experience Cloud?

Elasticsearch

Elasticsearch

Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).

Algolia

Algolia

Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.

Typesense

Typesense

It is an open source, typo tolerant search engine that delivers fast and relevant results out-of-the-box. has been built from scratch to offer a delightful, out-of-the-box search experience. From instant search to autosuggest, to faceted search, it has got you covered.

Amazon CloudSearch

Amazon CloudSearch

Amazon CloudSearch enables you to search large collections of data such as web pages, document files, forum posts, or product information. With a few clicks in the AWS Management Console, you can create a search domain, upload the data you want to make searchable to Amazon CloudSearch, and the search service automatically provisions the required technology resources and deploys a highly tuned search index.

Amazon Elasticsearch Service

Amazon Elasticsearch Service

Amazon Elasticsearch Service is a fully managed service that makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero down time.

Manticore Search

Manticore Search

It is a full-text search engine written in C++ and a fork of Sphinx Search. It's designed to be simple to use, light and fast, while allowing advanced full-text searching. Connectivity is provided via a MySQL compatible protocol or HTTP, making it easy to integrate.

Azure Search

Azure Search

Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. Quickly and easily tune search results and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios.

Swiftype

Swiftype

Swiftype is the easiest way to add great search to your website or mobile application.

MeiliSearch

MeiliSearch

It is a powerful, fast, open-source, easy to use, and deploy search engine. The search and indexation are fully customizable and handles features like typo-tolerance, filters, and synonyms.

Quickwit

Quickwit

It is the next-gen search & analytics engine built for logs. It is designed from the ground up to offer cost-efficiency and high reliability on large data sets. Its benefits are most apparent in multi-tenancy or multi-index settings.

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