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  4. Search As A Service
  5. Amazon CloudSearch vs Azure Cognitive Search

Amazon CloudSearch vs Azure Cognitive Search

OverviewComparisonAlternatives

Overview

Amazon CloudSearch
Amazon CloudSearch
Stacks130
Followers152
Votes27
Azure Cognitive Search
Azure Cognitive Search
Stacks39
Followers67
Votes1

Amazon CloudSearch vs Azure Cognitive Search: What are the differences?

Key Differences between Amazon CloudSearch and Azure Cognitive Search

Amazon CloudSearch and Azure Cognitive Search are both cloud-based search services that help developers build search capabilities into their applications. However, there are several key differences between these two services.

  1. Scalability:

    • Amazon CloudSearch offers automatic scaling capabilities, allowing developers to easily handle large amounts of data and traffic without worrying about infrastructure management.
    • Azure Cognitive Search also provides scalability features, but developers have more control and flexibility in managing their resources, allowing them to scale up or down based on their specific requirements.
  2. Data Sources:

    • Amazon CloudSearch supports a limited number of data sources, including Amazon S3 and Amazon RDS, making it suitable for applications primarily running on AWS.
    • Azure Cognitive Search offers a wide range of data source connectors, including databases, Azure Blob storage, and more, making it compatible with a broader range of data sources and integration scenarios.
  3. Advanced Search Features:

    • Amazon CloudSearch provides a robust set of search features, including faceted search, fuzzy matching, and partial word matching. However, some advanced features like document extraction and linguistic analysis require additional configuration and integration with other AWS services.
    • Azure Cognitive Search includes advanced search capabilities out of the box, such as semantic search, natural language processing, and entity recognition, enabling developers to build more sophisticated search experiences without requiring additional services.
  4. Geographic Distribution:

    • Amazon CloudSearch allows developers to deploy search instances in multiple availability zones, providing high availability and fault tolerance.
    • Azure Cognitive Search offers a global distribution feature, allowing developers to replicate their search indexes across multiple Azure regions, improving search performance and availability for users in different geographic locations.
  5. Pricing Model:

    • Amazon CloudSearch follows a pay-as-you-go pricing model, where users are charged based on the instance type, data transfer, and search requests.
    • Azure Cognitive Search also offers a consumption-based pricing model, but it provides more flexibility in terms of service tiers and pricing options, allowing developers to optimize cost based on their specific needs.
  6. Ecosystem Integration:

    • Amazon CloudSearch integrates well with other AWS services and offers native support for tools like AWS Identity and Access Management (IAM), CloudTrail, and CloudWatch.
    • Azure Cognitive Search seamlessly integrates with the wider Azure ecosystem and provides connectors to various Azure services like Azure Functions, Logic Apps, and Azure Active Directory for authentication and access control.

In summary, the key differences between Amazon CloudSearch and Azure Cognitive Search lie in their scalability options, available data sources, advanced search features, geographic distribution capabilities, pricing models, and ecosystem integration. Each service has its own strengths and considerations, depending on the specific requirements and preferences of developers and their applications.

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Detailed Comparison

Amazon CloudSearch
Amazon CloudSearch
Azure Cognitive Search
Azure Cognitive Search

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.

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.

Simple to Configure – You can make your data searchable using the AWS Management Console, API calls, or command line tools. Simply point to a sample set of data, and Amazon CloudSearch automatically proposes a list of index fields and a suggested configuration.;Automatic Scaling For Data & Traffic – Amazon CloudSearch scales up and down seamlessly as the amount of data or query volume changes.;Low Latency, High Throughput – Amazon CloudSearch always stores your index in RAM to ensure low latency and high throughput performance even at large scale. Amazon CloudSearch was created from the same A9 technology that powers search on Amazon.com.;Rich Search Features – Amazon CloudSearch indexes and searches both structured data and plain text. It includes most search features that developers have come to expect from a search engine, such as faceted search, free text search, Boolean search, customizable relevance ranking, query time rank expressions, field weighting, and sorting of results using any field. Amazon CloudSearch also provides near real-time indexing of document updates.;Secure – Amazon CloudSearch uses strong cryptographic methods to authenticate users and prevent unauthorized control of your domains. Amazon CloudSearch supports HTTPS and includes web service interfaces to configure firewall settings that control network access to your domain.
Start, maintain and scale with minimal investment;Create searchable content using integrated AI;Customise to meet goals and industry requirements
Statistics
Stacks
130
Stacks
39
Followers
152
Followers
67
Votes
27
Votes
1
Pros & Cons
Pros
  • 12
    Managed
  • 7
    Auto-Scaling
  • 5
    Compound Queries
  • 3
    Easy Setup
Pros
  • 1
    111
Integrations
No integrations available
Postman
Postman
Java
Java
Node.js
Node.js
Python
Python
C#
C#
PowerShell
PowerShell

What are some alternatives to Amazon CloudSearch, 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.

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.

Bonsai

Bonsai

Your customers expect fast, near-magical results from your search. Help them find what they’re looking for with Bonsai Elasticsearch. Our fully managed Elasticsearch solution makes it easy to create, manage, and test your app's search.

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