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Elastic Search 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

Elastic Search
Ranking in Search as a Service
1st
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
71
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (9th), Vector Databases (3rd)
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 July 2025, in the Search as a Service category, the mindshare of Elastic Search is 17.8%, up from 8.8% compared to the previous year. The mindshare of Solr is 6.4%, up from 6.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Search as a Service
 

Featured Reviews

Anand_Kumar - PeerSpot reviewer
Captures data from all other sources and becomes a MOM aka monitoring of monitors
Scalability and ROI are the areas they have to improve. Their license terms are based on the number of cores. If you increase the number of cores, it becomes very difficult to manage at a large scale. For example, if I have a $3 million project, I won't sell it because if we're dealing with a 10 TB or 50 TB system, there are a lot of systems and applications to monitor, and I have to make an MOM (Mean of Max) for everything. This is because of the cost impact. Also, when you have horizontal scaling, it's like a multi-story building with only one elevator. You have to run around, and it's not efficient. Even the smallest task becomes difficult. That's the problem with horizontal scaling. They need to improve this because if they increase the cores and adjust the licensing accordingly, it would make more sense.
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.

Quotes from Members

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

Pros

"I really like the visualization that you can do within it. That's really handy. Product-wise, it is a very good and stable product."
"ELK Elasticsearch is 100% scalable as scalability is built into the design"
"It is highly valuable because of its simplicity in maintenance, where most tasks are handled for you, and it offers a plethora of built-in features."
"The most valuable features are the detection and correlation features."
"Helps us to store the data in key value pairs and, based on that, we can produce visualisations in Kibana."
"The initial setup is fairly simple."
"The observability is the best available because it provides granular insights that identify reasons for defects."
"I appreciate that Elastic Enterprise Search is easy to use and that we have people on our team who are able to manage it effectively."
"​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. 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."
 

Cons

"I have not been using the solution for many years to know exactly the improvements needed. However, they could simplify how the YML files have to be structured properly."
"The solution has quite a steep learning curve. The usability and general user-friendliness could be improved. However, that is kind of typical with products that have a lot of flexibility, or a lot of capabilities. Sometimes having more choices makes things more complex. It makes it difficult to configure it, though. It's kind of a bitter pill that you have to swallow in the beginning and you really have to get through it."
"Elastic Enterprise Search's tech support is good but it could be improved."
"Elastic Search could benefit from a more user-friendly onboarding process for beginners."
"This product could be improved with additional security, and the addition of support for machine learning devices."
"The solution must provide AI integrations."
"Better dashboards or a better configuration system would be very good."
"Scalability and ROI are the areas they have to improve."
"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."
"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."
"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."
 

Pricing and Cost Advice

"​The pricing and license model are clear: node-based model."
"It can be expensive."
"The solution is affordable."
"The tool is an open-source product."
"We are using the free open-sourced version of this solution."
"An X-Pack license is more affordable than Splunk."
"The version of Elastic Enterprise Search I am using is open source which is free. The pricing model should improve for the enterprise version because it is very expensive."
"We are using the open-sourced version."
"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
Computer Software Company
16%
Financial Services Firm
14%
Manufacturing Company
9%
Government
9%
Computer Software Company
18%
Financial Services Firm
9%
Government
9%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about ELK Elasticsearch?
Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time anal...
What is your experience regarding pricing and costs for ELK Elasticsearch?
We used the open-source version of Elasticsearch, which was free.
What needs improvement with ELK Elasticsearch?
It would be useful if a feature for renaming indices could be added without affecting the performance of other features. However, overall, the consistency and stability of Elasticsearch are already...
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Comparisons

 

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
No data available
 

Overview

 

Sample Customers

T-Mobile, Adobe, Booking.com, BMW, Telegraph Media Group, Cisco, Karbon, Deezer, NORBr, Labelbox, Fingerprint, Relativity, NHS Hospital, Met Office, Proximus, Go1, Mentat, Bluestone Analytics, Humanz, Hutch, Auchan, Sitecore, Linklaters, Socren, Infotrack, Pfizer, Engadget, Airbus, Grab, Vimeo, Ticketmaster, Asana, Twilio, Blizzard, Comcast, RWE and many others.
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 Elastic Search vs. Solr and other solutions. Updated: July 2025.
861,481 professionals have used our research since 2012.