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Amazon Elasticsearch Service vs Solr comparison

Amazon Web Services (AWS) and Apache are both solutions in the Search as a Service category. Amazon Web Services (AWS) is ranked #3 with an average rating of 7.7, while Apache is ranked #8. Amazon Web Services (AWS) holds a 7.9% mindshare in SS, compared to Apache’s 6.2% mindshare. Additionally, 100% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Apache users who would recommend it.
Amazon Elasticsearch Service
Read 6 Amazon Elasticsearch Service reviews
  • 1,509 Views
  • 1,287 Comparison Views
100% willing to recommend
Solr
Read 4 Solr reviews
  • 747 Views
  • 577 Comparison Views
100% willing to recommend
 

Comparison Buyer's Guide

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Executive Summary
We performed a comparison between Amazon Elasticsearch Service and Solr based on real PeerSpot user reviews.

Find out in this report how the two Search as a Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

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To learn more, read our detailed Amazon Elasticsearch Service vs. Solr Report (Updated: April 2025).
Buyer's Guide
Amazon Elasticsearch Service vs. Solr
April 2025
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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 Elasticsearch Service
Ranking in Search as a Service
3rd
Average Rating
8.2
Number of Reviews
6
Ranking in other categories
No ranking in other categories
Solr
Ranking in Search as a Service
8th
Average Rating
7.8
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2025, in the Search as a Service category, the mindshare of Amazon Elasticsearch Service is 7.9%, down from 17.5% compared to the previous year. The mindshare of Solr is 6.2%, down from 6.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Search as a Service
 

Featured Reviews

Surjit Choudhury - PeerSpot reviewer
A solution beneficial for the streaming of data that needs to improve its configuration part
Not for all the projects I saw, but most of the projects were using Elasticsearch, which is very common. In my case, I have faced two scenarios with the solution. Other than that, generic solutions like SNS, SQS, and Lambda are some of the very generic tools we are using. Regarding what I would like to see improved in the solution, I would say that, basically, the configuration part is an area with a shortcoming. We have a DevOps person, so all these things are configured in the Terraform through the Terraform script we use. The DevOps team used to take care of it. To run the process or run the services and how to use the services are the parts for which we are using the solution. Some upgradation is required on the configuration side so that we can get to use it. In that case, I have to check on that area with the DevOps.
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reviewer1368636 - PeerSpot reviewer
Good indexing and decent stability, but requires more documentation
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. MongoDB can realize more complex operations than Solr can. Solr should add some more complex operations to the database to at least bring it up to MondoDB's level of functionality. It would make it more competitive. There might be some compatibility issues between the data types within Solr. This needs to be improved. Solr has a schema that we have to load the schema as an HTML, or SML file. This usually needs to be done by our engineers. It should be easier to do without needing too much technical background.
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Quotes from Members

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

Pros

"It enables us to efficiently search and retrieve our event data, offering us a versatile approach to locate specific information within these logs."
"In case there is a failure, Elastic manages everything well, and there no major downtime."
"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's a good log management platform. In terms of infrastructure management, it's good."
"The stability of the product is good."
"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."
"The initial set up is very easy...We really appreciate Amazon!"
"They have the good documentation in the help text and that is the reason the Amazon is the perfect solution in the current market."
"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."
"It has improved our search ranking, relevancy, search performance, and user retention."
"​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."
 

Cons

"The configuration should be more straightforward because we had to select a lot of things."
"I want to see a new feature in Amazon Elasticsearch Service that allows users to create default filters for filtered levels."
"There is a problem with the database. Amazon only provides the hosting to run our applications bias, but there is no option to manage the database within the Elasticsearch product."
"Amazon Elasticsearch can improve the bullion in the near search and the ease of integration with Kibana. Additionally, there could be more flexibility in the configuration and documentation."
"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."
"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."
"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."
"SolrCloud stability, indexing and commit speed, and real-time Indexing need improvement."
"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."
"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."
"The performance for this solution, in terms of queries, could be improved."
 

Pricing and Cost Advice

"Compared to other cloud platforms, it is manageable and not very expensive."
"You only pay for what you use."
"There is a community edition available and the price of the commercial offering is reasonable."
"The solution is not expensive, but priced averagely, I will say."
"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
20%
Computer Software Company
13%
Manufacturing Company
13%
Government
9%
Computer Software Company
20%
Financial Services Firm
10%
Manufacturing Company
7%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

What do you like most about Amazon Elasticsearch Service?
It enables us to efficiently search and retrieve our event data, offering us a versatile approach to locate specific information within these logs.
See all answers
What is your experience regarding pricing and costs for Amazon Elasticsearch Service?
The solution is not expensive, but priced averagely, I will say. Regarding the pricing part based on the use cases, we used to sometimes see or do some of the costing parts also in that case. Depar...
See all answers
What needs improvement with Amazon Elasticsearch Service?
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...
See all answers
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Comparisons

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Compared 20% of the time
Amazon AWS CloudSearch vs Solr Logo
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Compared 18% of the time
Azure Search vs Solr Logo
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Compared 18% of the time
Amazon Kendra vs Solr Logo
Amazon Kendra vs Solr
Compared 18% of the time
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Product Reports

Buyer's Guide
Search as a Service
April 2025
Amazon Elasticsearch Service reportDownload Amazon Elasticsearch Service product report
Buyer's Guide
Search as a Service
April 2025
Solr reportDownload Solr product report
 

Overview

Amazon Elasticsearch Service is a managed service that makes it easy to deploy, operate, and scale Elasticsearch clusters in the AWS Cloud.

Amazon Web Services (AWS)
Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.
Apache
 

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
Buyer's Guide
Amazon Elasticsearch Service vs. Solr
April 2025
Free Report: Amazon Elasticsearch Service vs. Solr
Find out what your peers are saying about Amazon Elasticsearch Service vs. Solr and other solutions. Updated: April 2025.
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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.