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Amazon OpenSearch Service vs Azure AI Search comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Jun 3, 2026

Review summaries and opinions

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

Categories and Ranking

Amazon OpenSearch Service
Ranking in Search as a Service
3rd
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
13
Ranking in other categories
Application Performance Monitoring (APM) and Observability (29th), Log Management (17th)
Azure AI Search
Ranking in Search as a Service
4th
Average Rating
7.6
Number of Reviews
12
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2026, in the Search as a Service category, the mindshare of Amazon OpenSearch Service is 13.4%, up from 5.6% compared to the previous year. The mindshare of Azure AI Search is 12.8%, up from 9.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Search as a Service Mindshare Distribution
ProductMindshare (%)
Amazon OpenSearch Service13.4%
Azure AI Search12.8%
Other73.8%
Search as a Service
 

Featured Reviews

Md. Shahariar Hossen - PeerSpot reviewer
Senior Software Engineer at Cefalo
Event tracking has become smoother and data analytics provide clear insights for user actions
Amazon OpenSearch Service is not providing the processing feature directly. From Amazon OpenSearch Service, we are actually maintaining the AWS SQS, the queue service, which is responsible for providing information about what data has to be modified. So using that SQS, we're actually providing it, but we're not directly using Amazon OpenSearch Service for keeping data to other data pipeline thing. So far we didn't use it for any machine learning purposes, but in future, we have plans to extend or implement this feature. Since AWS itself is secure and Amazon OpenSearch Service is a part of this entire ecosystem, it becomes much easier for security purposes. From the validation point of view, Amazon OpenSearch Service itself provides easy to communicate APIs and up-to-date documents, which is much beneficial. For example, if I'm missing anything, I can directly go and check the documentation. That is actually much easier. I would rate it as really good so far. It's much faster. For our local machine, we can also use a kind of replica of Amazon OpenSearch Service just for development purposes. That is another good feature. I would say for the encryption thing and also the user access control management, it's much faster. For some of these hashing algorithms, it also worked really well so far. To be honest, I didn't find any places where it can be improved. However, I think they could provide more abstraction. For example, still for searching, we have to write down the queries in a specific manner, such as for a specific JSON structure or in a specific way. Otherwise, they don't provide us the actual results. For at least this purpose, I think abstraction could be a bit easier or a bit improved. Other than that, right now there is the age of AI, so some kind of prompting could also work, but I'm not sure how it could be integrated. As a user, lower prices or reasonable pricing is always better. Those can be improved as well. However, it is good that most of the services including Amazon OpenSearch Service actually provide pay as you go pricing. So if there were a bit lower version or a bit less payment methodology, it might be much better.
Harshal Chandekar - PeerSpot reviewer
AI Consultant at a tech vendor with 10,001+ employees
Rag workflows have improved document search and reduced development effort for client projects
In my experience, the best features Azure AI Search offers are that it is very easy to upload documents and they can obviously be very agile and we can query upon these documents very easily. When I say it is easy to upload and query documents, it makes the application more reliable in the case that if we have a certain study or certain use case wherein just that PDF or just those amount of information will be used and not the entire thing, so the user can just go quickly and search for that documentation. I think it is fully integrated with Azure and we use Azure primarily for our primary cloud platform, so that helps very much in integrating and in maintaining one service provider. Regarding Azure AI Search's AI capabilities, it provides good security in terms of reliability and scalability as well, so there are no concerns for it regarding those issues. Regarding Azure AI Search's AI capabilities, it is accurate and reliable 99% of the time.

Quotes from Members

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

Pros

"AWS has now made our life easy."
"The business analytics capabilities are the most important feature it provides."
"In case there is a failure, Elastic manages everything well, and there no major downtime."
"The initial set up is very easy...We really appreciate Amazon!"
"The customer service is excellent, rated nine out of ten."
"We retrieve historical data with just a click of a button to move it from cold to hot or warm because it's already stored in the backend storage"
"Regarding valuable features of the solution, we found with the process, which we have used in both cases where we used the solution that while you're seeing the streaming of data, you can analyze in the initial phase what sort of data you are streaming and whether it is valuable."
"It enables us to efficiently search and retrieve our event data, offering us a versatile approach to locate specific information within these logs."
"Because all communication is done via the REST API, data is retrieved quickly in JSON format to reduce overhead and latency.​"
"It provides good access capabilities to various platforms."
"Azure Search is well-documented, making it easy to understand and implement."
"Azure AI Search has impacted my organization positively with overall time saving and low costs as the main outputs that we get after using it."
"The solution's initial setup is straightforward."
"Usually, that search functionality used to take around 10 secs to search data, and that time has been reduced to a few milliseconds now."
"The customer engagement was good."
"Since using Azure AI Search, time saving will be the main differentiator among other types of tools I've tried before, and it's also a very holistic tool, so it covers many use cases."
 

Cons

"We faced documentation challenges during integration after migrating from Elasticsearch to Amazon OpenSearch Service. Better documentation on integration, query handling, and a more user-friendly UI could enhance the product."
"The configuration should be more straightforward because we had to select a lot of things."
"The price is fair yet leans towards the expensive side. I'd rate it five out of ten with respect to capabilities vs. cost."
"I would say that, basically, the configuration part is an area with a shortcoming...Some upgradation is required on the configuration side so that we can get to use it."
"As a user, lower prices or reasonable pricing is always better."
"It would be beneficial to have some level of customization available in the managed service, tailored to the specific use cases of the end users."
"The pricing aspect is a concern. The service is way too costly. For the past month, I used only 30 to 40 MB of data, and the cost was $500. AWS could improve pricing."
"They can enhance data visualization."
"The solution's stability could be better."
"Azure AI Search could be improved primarily because the UX and UI could be a little bit more intuitive for persons since the learning curve could be a little bit high."
"We used the semantic search capabilities of Azure AI Search, but we haven't gotten good results in the semantic search."
"The after-hour services are slow."
"On a scale from one to ten where one is the worst and ten is the best, I would rate Azure Search as probably a six-out-of-ten."
"Azure AI Search could be improved regarding compatibility with Azure Blob Storage in order to keep the prompts and everything that I am using for building the tool safe."
"The initial setup is not as easy as it should be."
"I think Azure AI Search can be improved by implementing it with the agents as well, and I think that their agent integration is something they could work upon or they can improve it very easily or without managing anything, but apart from that, it is building basic functionalities of RAG, but if that would be expanded to agents as well, then that would be very useful."
 

Pricing and Cost Advice

"Compared to other cloud platforms, it is manageable and not very expensive."
"The solution is not expensive, but priced averagely, I will say."
"There is a community edition available and the price of the commercial offering is reasonable."
"You only pay for what you use."
"The solution is affordable."
"For the actual costs, I encourage users to view the pricing page on the Azure site for details.​"
"The cost is comparable."
"I think the solution's pricing is ok compared to other cloud devices."
"​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."
"I would rate the pricing an eight out of ten, where one is the low price, and ten is the high price."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Manufacturing Company
10%
Computer Software Company
8%
Comms Service Provider
7%
Financial Services Firm
11%
Computer Software Company
10%
Outsourcing Company
9%
Comms Service Provider
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business7
Midsize Enterprise2
Large Enterprise4
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise5
Large Enterprise5
 

Questions from the Community

What is your experience regarding pricing and costs for Amazon OpenSearch Service?
I would consider the pricing as a six based on how much data we are handling; if we handle minimal data, it's cheap, but for large data, it becomes costly. Our clients usually pay between $1,000 to...
What needs improvement with Amazon OpenSearch Service?
Amazon OpenSearch Service is not providing the processing feature directly. From Amazon OpenSearch Service, we are actually maintaining the AWS SQS, the queue service, which is responsible for prov...
What is your primary use case for Amazon OpenSearch Service?
Amazon OpenSearch Service is a user-friendly version of Elasticsearch, as per my understanding. I have been using it for our volunteer management system where around 5,000 to 6,000 users are using ...
What needs improvement with Azure Search?
I think Azure AI Search can be improved by implementing it with the agents as well, and I think that their agent integration is something they could work upon or they can improve it very easily or ...
What is your primary use case for Azure Search?
My main use case for Azure AI Search is building RAG workflows which are useful for client work. I used Azure AI Search in finding documents about a user manual in which the problem statement was i...
What advice do you have for others considering Azure Search?
On a scale of 1 to 10, I rate Azure AI Search a nine. I chose a nine for Azure AI Search primarily because of the agents and the use cases are very limited, I would say to RAG as of now. Azure AI S...
 

Also Known As

Amazon Elasticsearch Service
No data available
 

Overview

 

Sample Customers

VIDCOIN, Wyng, Yellow New Zealand, zipMoney, Cimri, Siemens, Unbabel
XOMNI, Real Madrid C.F., Weichert Realtors, JLL, NAV CANADA, Medihoo, autoTrader Corporation, Gjirafa
Find out what your peers are saying about Amazon OpenSearch Service vs. Azure AI Search and other solutions. Updated: September 2026.
920,929 professionals have used our research since 2012.