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Amazon OpenSearch Service vs Solr comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Nov 16, 2025

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 (26th), Log Management (22nd)
Solr
Ranking in Search as a Service
10th
Average Rating
7.8
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the Search as a Service category, the mindshare of Amazon OpenSearch Service is 8.7%, down from 10.8% compared to the previous year. The mindshare of Solr is 4.8%, down from 6.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Search as a Service Market Share Distribution
ProductMarket Share (%)
Amazon OpenSearch Service8.7%
Solr4.8%
Other86.5%
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.
reviewer823641 - PeerSpot reviewer
Senior Search Engineer at a financial services firm with 51-200 employees
The Natural Language Search capability is helpful and intuitive for our users
The initial setup is complex because this is a distributed system, and you have to make sure that every individual node is aware of every other node in existence. This search engine has a large capacity, so you need to make sure that there is enough buffer space. We took one month to deploy and perform a fresh setup. Our strategy was to start with a local data center, before venturing into cross data center replicas. A staff size of two to four people is suitable for deploying and maintaining the solution, depending upon the scale. They would set up the solution and put monitoring in place for the indexing jobs, as well as design the schema so that the data can feed well.

Quotes from Members

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

Pros

"The most valuable features of Amazon Elasticsearch are ease of use, native JSON, and efficiency. Additionally, handles many use cases and search grammar was useful."
"It's actually easier to collaborate since it is already deployed in the AWS cloud itself."
"It enables us to efficiently search and retrieve our event data, offering us a versatile approach to locate specific information within these logs."
"The customer service is excellent, rated nine out of ten."
"Our customers have seen tangible benefits from Amazon OpenSearch Service, especially in terms of their applications running smoothly, so they do get a return on investment."
"The initial set up is very easy...We really appreciate Amazon!"
"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"
"The business analytics capabilities are the most important feature it provides."
"One of the best aspects of the solution is the indexing. It's already indexed to all the fields in the category. We don't need to spend so much extra effort to do the indexing. It's great."
"The most valuable feature is the ability to perform a natural language search."
"​Sharding data, Faceting, Hit Highlighting, parent-child Block Join and Grouping, and multi-mode platform are all valuable features."
"It has improved our search ranking, relevancy, search performance, and user retention."
 

Cons

"The configuration should be more straightforward because we had to select a lot of things."
"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."
"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."
"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."
"One improvement I would like to see is support for auto-scaling."
"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."
"One glaring issue was with our mapping configuration as the system accepted the data we posted, but after a few months, when we attempted complex queries, we realized the date formatting had become problematic."
"Encountered issues with both master-slave and SolrCloud. Indexing and serving traffic from same collection has very poor performance. Some components are slow for searching."
"It does take a little bit of effort to use and understand the solution. It would help us a lot if the solution offered up more documentation or tutorials to help with training or troubleshooting."
"The performance for this solution, in terms of queries, could be improved."
"SolrCloud stability, indexing and commit speed, and real-time Indexing need improvement."
"With increased sharding, performance degrades. Merger, when present, is a bottle-neck. Peer-to-peer sync has issues in SolrCloud when index is incrementally updated."
 

Pricing and Cost Advice

"Compared to other cloud platforms, it is manageable and not very expensive."
"You only pay for what you use."
"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."
"The only costs in addition to the standard licensing fees are related to the hardware, depending on whether it is cloud-based, or on-premise."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
11%
Manufacturing Company
10%
Government
7%
Computer Software Company
16%
Manufacturing Company
12%
Retailer
10%
Comms Service Provider
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise2
Large Enterprise2
No data available
 

Questions from the Community

What do you like most about Amazon OpenSearch Service?
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
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?
In terms of data handling capabilities with Amazon OpenSearch Service, they can be complex and managing data in comparison to other SIM solutions is a major drawback, as it is very hard to handle t...
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Also Known As

Amazon Elasticsearch Service
No data available
 

Overview

 

Sample Customers

VIDCOIN, Wyng, Yellow New Zealand, zipMoney, Cimri, Siemens, Unbabel
eHarmony, Sears, StubHub, Best Buy, Instagram, Netflix, Disney, AT&T, eBay, AOL, Bloomberg, Comcast, Ticketmaster, Travelocity, MTV Networks
Find out what your peers are saying about Amazon OpenSearch Service vs. Solr and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.