Compare Amazon AWS CloudSearch vs. Azure Search

Amazon AWS CloudSearch is ranked 3rd in Search as a Service with 3 reviews while Azure Search is ranked 2nd in Search as a Service with 2 reviews. Amazon AWS CloudSearch is rated 8.6, while Azure Search is rated 9.0. The top reviewer of Amazon AWS CloudSearch writes "Has worldwide stability and many layers of security, like hardware security and software security". On the other hand, the top reviewer of Azure Search writes "Offers a tremendous amount of flexibility and scalability when integrating with applications". Amazon AWS CloudSearch is most compared with Algolia, Amazon Elasticsearch Service and Solr, whereas Azure Search is most compared with ELK Elasticsearch, Solr and Amazon AWS CloudSearch. See our Amazon AWS CloudSearch vs. Azure Search report.
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Most Helpful Review
AmrAhmed
Find out what your peers are saying about Amazon AWS CloudSearch vs. Azure Search and other solutions. Updated: November 2019.
384,147 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
It's the best solution for any company. It has a hosting ERP system for any task. AWS is stable. AWS is more flexible and its elastic concept is a new concept. AWS is also very secure. It has many layers of security, like hardware security and software security. This is a big issue.CDN service reduces latency when accessing our web application.Document indexing, text-based search API, and Geospatial searches are all good features.

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Offers a tremendous amount of flexibility and scalability when integrating with applications.The product is extremely configurable, allowing you to customize the search experience to suit your needs.Because all communication is done via the REST API, data is retrieved quickly in JSON format to reduce overhead and latency.​The search functionality time has been reduced to a few milliseconds.Creates indexers to get data from different data sources.

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Cons
Maybe they are common in Egypt, but you should make a request on Amazon to create a function to monitor CPU performance, memory, and files. It is very difficult in AWS. I would tell them it should be simple, just drag and drop. I think they could develop this option so we can drag and drop to monitor performance of the processor and memory.Regarding the period of propagation on CDN servers, sometimes we update photos or files and we don't see the update instantly. We need to wait for sometime.Latlon data type only supports single value per document. All other types support multiple values. We faced issues with this because we had scenarios where, for each document, we needed to store multiple latlon values for different geographical locations.Index cleanup is sometimes painful. No easy way to clean indexes or a bulk of documents. Full indexing or regeneration of entire indexes sometimes gets stuck. In one instance, we had to delete the entire index and re-create it.

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For SDKs, Azure Search currently offers solutions for .NET and Python. Additional platforms would be welcomed, especially native iOS and Android solutions for mobile development.For availability, expanding its use to all Azure datacenters would be helpful in increasing awareness and usage of the product.​Adding items to Azure Search using its .NET APIs sometimes throws exceptions.

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Pricing and Cost Advice
We chose AWS because of its cost and stability.

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​When telling people about the product, I always encourage them to set up a new service using the free pricing tier. This allows them to learn about the product and its capabilities in a risk-free environment. Depending on their needs, the free tier may be suitable for their projects, however enterprise applications will most likely required a higher, paid tier.For the actual costs, I encourage users to view the pricing page on the Azure site for details.​

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Ranking
3rd
out of 10 in Search as a Service
Views
1,368
Comparisons
1,097
Reviews
3
Average Words per Review
600
Avg. Rating
8.7
2nd
out of 10 in Search as a Service
Views
2,926
Comparisons
2,361
Reviews
2
Average Words per Review
506
Avg. Rating
9.0
Top Comparisons
Compared 23% of the time.
Compared 20% of the time.
Compared 62% of the time.
Compared 29% of the time.
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Amazon
Microsoft
Overview

Amazon CloudSearch is a managed service in the AWS Cloud that makes it simple and cost-effective to set up, manage, and scale a search solution for your website or application.
Amazon CloudSearch supports 34 languages and popular search features such as highlighting, autocomplete, and geospatial search. With Amazon CloudSearch, you can quickly add rich search capabilities to your website or application. You don't need to become a search expert or worry about hardware provisioning, setup, and maintenance. With a few clicks in the AWS Management Console, you can create a search domain and upload the data that you want to make searchable, and Amazon CloudSearch will automatically provision the required resources and deploy a highly tuned search index.

You can easily change your search parameters, fine tune search relevance, and apply new settings at any time. As your volume of data and traffic fluctuates, Amazon CloudSearch seamlessly scales to meet your needs.

Azure Search is a search-as-a-service cloud solution that gives developers APIs and tools for adding a rich search experience over your data in web, mobile, and enterprise applications. Functionality is exposed through a simple REST API or .NET SDK that masks the inherent complexity of search technology. In addition to APIs, the Azure portal provides administration and prototyping support. Infrastructure and availability are managed by Microsoft.
Offer
Learn more about Amazon AWS CloudSearch
Learn more about Azure Search
Sample Customers
SmugMugXOMNI, Real Madrid C.F., Weichert Realtors, JLL, NAV CANADA, Medihoo, autoTrader Corporation, Gjirafa
Find out what your peers are saying about Amazon AWS CloudSearch vs. Azure Search and other solutions. Updated: November 2019.
384,147 professionals have used our research since 2012.
We monitor all Search as a Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
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