Try our new research platform with insights from 80,000+ expert users

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 June 2025, in the Search as a Service category, the mindshare of Elastic Search is 16.3%, up from 8.5% compared to the previous year. The mindshare of Solr is 5.9%, down from 6.5% 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

"It helps us to analyse the logs based on the location, user, and other log parameters."
"X-Pack provides good features, like authorization and alerts."
"The most valuable features are the ease and speed of the setup."
"Implementing the main requirements regarding my support portal​."
"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."
"Search is really powerful."
"The flexibility and the support for diverse languages that it provides for searching the database are most valuable. We can use different languages to query the database."
"It provides deep visibility into your cloud and distributed applications, from microservices to serverless architectures. It quickly identifies and resolves the root causes of issues, like gaining visibility into all the cloud-based and on-prem applications."
"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."
"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."
 

Cons

"It should be easier to use. It has been getting better because many functions are pre-defined, but it still needs improvement."
"Both the graph feature and the reporting feature are a little bit lacking. The alerting also needs to be improved."
"The reports could improve."
"The price could be better. Kibana has some limitations in terms of the tablet to view event logs. I also have a high volume of data. On the initialization part, if you chose Kibana, you'll have some limitations. Kibana was primarily proposed as a log data reviewer to build applications to the viewer log data using Kibana. Then it became a virtualization tool, but it still has limitations from a developer's point of view."
"Ratio aggregation is not supported in this solution."
"There are a lot of manual steps on the operating system. It could be simplified in the user interface."
"An improvement would be to have an interface that allows easier navigation and tracing of logs."
"Machine learning on search needs 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."
"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."
"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."
"The performance for this solution, in terms of queries, could be improved."
 

Pricing and Cost Advice

"I rate Elastic Search's pricing an eight out of ten."
"we are using a licensed version of the product."
"The cost varies based on factors like usage volume, network load, data storage size, and service utilization. If your usage isn't too extensive, the cost will be lower."
"Elastic Search is open-source, but you need to pay for support, which is expensive."
"There is a free version, and there is also a hosted version for which you have to pay. We're currently using the free version. If things go well, we might go for the paid version."
"We are paying $1,500 a month to use the solution. If you want to have endpoint protection you need to pay more."
"The solution is less expensive than Stackdriver and Grafana."
"We use the free version for some logs, but not extensive use."
"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."
report
Use our free recommendation engine to learn which Search as a Service solutions are best for your needs.
856,873 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Computer Software Company
16%
Financial Services Firm
15%
Government
9%
Manufacturing Company
8%
Computer Software Company
18%
Financial Services Firm
9%
Retailer
8%
Government
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...
Ask a question
Earn 20 points
 

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: June 2025.
856,873 professionals have used our research since 2012.