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Elastic Search vs Solr comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Elastic Search
Ranking in Search as a Service
1st
Average Rating
8.2
Reviews Sentiment
7.2
Number of Reviews
65
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (11th), Vector Databases (1st)
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 November 2024, in the Search as a Service category, the mindshare of Elastic Search is 12.2%, up from 7.7% compared to the previous year. The mindshare of Solr is 6.9%, up from 6.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Search as a Service
 

Featured Reviews

Saurav Kumar - PeerSpot reviewer
Provides us with the capability to execute multiple queries according to our requirements
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 analytics with Elastic benefits us due to the huge traffic volume in our organization, which reaches up to 60,000 requests per second. With logs of approximately 25 GB per day, manually analyzing traffic behavior, payloads, headers, user agents, and other details is impractical.
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 am impressed with the product's Logstash. The tool is fast and customizable. You can build beautiful dashboards with it. It is useful and reliable."
"The ability to aggregate log and machine data into a searchable index reduces time to identify and isolate issues for an application. Saves time in triage and incident response by eliminating manual steps to access and parse logs on separate systems, within large infrastructure footprints."
"It's a stable solution and we have not had any issues."
"Elastic Enterprise Search is scalable. On a scale of one to 10, with one being not scalable and 10 being very scalable, I give Elastic Enterprise Search a 10."
"Implementing the main requirements regarding my support portal​."
"The initial setup is very easy for small environments."
"The solution has great scalability."
"A good use case is saving metadata of your systems for data cataloging. Various systems, like those opened in metadata and similar applications, use Elasticsearch to store their text data."
"​Sharding data, Faceting, Hit Highlighting, parent-child Block Join and Grouping, and multi-mode platform are all valuable features."
"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."
"The most valuable feature is the ability to perform a natural language search."
 

Cons

"Elastic Search could benefit from a more user-friendly onboarding process for beginners."
"The reports could improve."
"The one area that can use improvement is the automapping of fields."
"Elastic Enterprise Search can improve by adding some kind of search that can be used out of the box without too much struggle with configuration. With every kind of search engine, there is some kind of special function that you need to do. A simple out-of-the-box search would be useful."
"The different applications need to be individually deployed."
"We'd like to see more integration in the future, especially around service desks or other ITSM tools."
"Machine learning on search needs improvement."
"There is an index issue in which the data starts to crash as it increases."
"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."
"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."
"SolrCloud stability, indexing and commit speed, and real-time Indexing need improvement."
 

Pricing and Cost Advice

"we are using a licensed version of the product."
"The basic license is free, but it comes with a lot of features that aren't free. With a gold license, we get active directory integration. With a platinum license, we get alerting."
"I rate Elastic Search's pricing an eight out of ten."
"The solution is free."
"It can be expensive."
"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."
"This product is open-source and can be used free of charge."
"An X-Pack license is more affordable than Splunk."
"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
18%
Financial Services Firm
15%
Manufacturing Company
9%
Government
7%
Computer Software Company
18%
Financial Services Firm
14%
Real Estate/Law Firm
8%
Insurance Company
6%
 

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?
I am not directly involved with pricing or setup costs. While I know a portion is open-source, a paid version might be necessary.
What needs improvement with ELK Elasticsearch?
An improvement would be to have an interface that allows easier navigation and tracing of logs. The current system requires manually inputting dates to verify alerts. A visual timeline that pinpoin...
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Comparisons

 

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
No data available
 

Learn More

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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: October 2024.
816,406 professionals have used our research since 2012.