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Amazon AWS CloudSearch vs Solr comparison

 

Comparison Buyer's Guide

Executive Summary

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 AWS CloudSearch
Ranking in Search as a Service
7th
Average Rating
8.4
Number of Reviews
13
Ranking in other categories
No ranking in other categories
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 August 2026, in the Search as a Service category, the mindshare of Amazon AWS CloudSearch is 5.5%, down from 8.0% compared to the previous year. The mindshare of Solr is 5.2%, down from 6.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Search as a Service Mindshare Distribution
ProductMindshare (%)
Amazon AWS CloudSearch5.5%
Solr5.2%
Other89.3%
Search as a Service
 

Featured Reviews

HM
Software Developer at ECFY Consulting Private Limited
Search workflows have become faster and our team manages operational records more efficiently
Improvements for Amazon AWS CloudSearch can be made, but I will first start with the biggest improvement. The biggest improvement area is that Amazon AWS CloudSearch feels a little older compared to newer AWS services. The second thing about improvement is the documentation. The documentation could definitely be refreshed with more practical examples and troubleshooting scenarios. During setup, a few indexing issues took longer to diagnose because error messages were pretty generic. Better debugging visibility would reduce trial-and-error work. Monitoring is decent through Amazon CloudWatch, but I would like more detailed search-level diagnostics out of the box. Sometimes it is not obvious why certain queries rank results differently unless you manually test a lot. More transparent query analysis, indexing, and insights would be useful. Logging exists, but deeper visibility would help during optimization.
it_user823641 - 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

"We were able to build the core search functionality using this product."
"The quality of the solution is good."
"CDN service reduces latency when accessing our web application."
"Storage of photos and files which can be accessed anyplace, anytime, extremely quickly."
"I've found the solution to be very scalable."
"AWS CloudSearch's best features are good performance under high CPU and memory use, and ease of deployment and scaling."
"It is remarkably efficient and beneficial."
"It will remain alive in the market. The solution will be stable in the market."
"​Sharding data, Faceting, Hit Highlighting, parent-child Block Join and Grouping, and multi-mode platform are all valuable features."
"The most valuable feature is the ability to perform a natural language search."
"One of the best aspects of the solution is the indexing; it's already indexed to all the fields in the category, so we don't need to spend so much extra effort to do the indexing, which is great."
"This is an infinitely scalable product with state-of-the-art technology, and the value of Natural Language Search is tremendous."
"We use Solr to index over 600k documents; it's very fast, flexible to use, and the speed of indexing individual documents has been great."
"It has improved our search ranking, relevancy, search performance, and user retention."
 

Cons

"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."
"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."
"In terms of what needs improvement, I would say that it needs to keep its cost competitive in the market, especially in comparison to other clouds."
"The biggest improvement area is that Amazon AWS CloudSearch feels a little older compared to newer AWS services."
"Amazon's technical support needs to improve as they only solve about half our problems."
"I do not have any suggestions for improvements at this time."
"The price of the solution can be expensive."
"The solution should improve the recovery aspects that it has on offer."
"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."
"The performance for this solution, in terms of queries, could be improved."
"The solution's grammar and syntax should be easier."
"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."
"SolrCloud stability, indexing and commit speed, and real-time Indexing need improvement."
"Memory utilization could be better but it is an industrial strength tool so some overhead is to be expected."
"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

"I'm not sure how much we pay a year. It might be around $30,000 a year."
"There was no license needed to use this solution."
"We chose AWS because of its cost and stability."
"Our license costs around $4,000 per month."
"On a scale of one to ten, where one point is cheap, and ten points are expensive, I rate the pricing as medium or reasonable."
"Amazon AWS CloudSearch charging is based on how many resources you consume or and the solution is known to be a bit expensive."
"In comparison to IBM and Microsoft, the pricing is more favorable."
"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
Outsourcing Company
10%
Comms Service Provider
10%
Educational Organization
8%
Construction Company
8%
Outsourcing Company
13%
Comms Service Provider
11%
Construction Company
11%
Computer Software Company
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise2
Large Enterprise6
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for Amazon AWS CloudSearch?
We purchased Amazon AWS CloudSearch through the AWS Marketplace. Pricing was understandable once we estimated indexing volume and query traffic. Though it can grow if you scale instances aggressive...
What needs improvement with Amazon AWS CloudSearch?
Improvements for Amazon AWS CloudSearch can be made, but I will first start with the biggest improvement. The biggest improvement area is that Amazon AWS CloudSearch feels a little older compared t...
What is your primary use case for Amazon AWS CloudSearch?
The main use case for us was to search the operational records from our company databases and perform full-text search across operational records and uploaded documents. We needed something where u...
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Overview

 

Sample Customers

SmugMug
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 AWS CloudSearch vs. Solr and other solutions. Updated: June 2026.
907,816 professionals have used our research since 2012.