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  1. Stackups
  2. Utilities
  3. Search
  4. Search As A Service
  5. Azure Cognitive Search vs Groonga

Azure Cognitive Search vs Groonga

OverviewComparisonAlternatives

Overview

Groonga
Groonga
Stacks2
Followers15
Votes0
GitHub Stars831
Forks120
Azure Cognitive Search
Azure Cognitive Search
Stacks39
Followers67
Votes1

Groonga vs Azure Cognitive Search: What are the differences?

What is Groonga? * An open-source full-text search engine and column store*. It is an embeddable super fast full text search engine. It can be embedded into MySQL. Mroonga is a storage engine that is based on it.

What is 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.

Groonga and Azure Cognitive Search belong to "Search as a Service" category of the tech stack.

Some of the features offered by Groonga are:

  • Storage Engine
  • Fast
  • Easy to use

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

Groonga is an open source tool with 579 GitHub stars and 111 GitHub forks. Here's a link to Groonga's open source repository on GitHub.

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Detailed Comparison

Groonga
Groonga
Azure Cognitive Search
Azure Cognitive Search

It is an embeddable super fast full text search engine. It can be embedded into MySQL. Mroonga is a storage engine that is based on it.

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.

Storage Engine; Fast; Easy to use
Start, maintain and scale with minimal investment;Create searchable content using integrated AI;Customise to meet goals and industry requirements
Statistics
GitHub Stars
831
GitHub Stars
-
GitHub Forks
120
GitHub Forks
-
Stacks
2
Stacks
39
Followers
15
Followers
67
Votes
0
Votes
1
Pros & Cons
No community feedback yet
Pros
  • 1
    111
Integrations
Snowplow
Snowplow
Kibana
Kibana
Couchbase
Couchbase
Cloud 66
Cloud 66
Datadog
Datadog
Redash
Redash
Logstash
Logstash
Postman
Postman
Java
Java
Node.js
Node.js
Python
Python
C#
C#
PowerShell
PowerShell

What are some alternatives to Groonga, Azure Cognitive Search?

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.

Sphinx

Sphinx

It lets you either batch index and search data stored in an SQL database, NoSQL storage, or just files quickly and easily — or index and search data on the fly, working with it pretty much as with a database server.

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.

MkDocs

MkDocs

It builds completely static HTML sites that you can host on GitHub pages, Amazon S3, or anywhere else you choose. There's a stack of good looking themes available. The built-in dev-server allows you to preview your documentation as you're writing it. It will even auto-reload and refresh your browser whenever you save your changes.

Swiftype

Swiftype

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

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