Solr Reviews

Name: Solr
Brand: Apache
Rating: 3.9 (4 reviews)

Vendor: Apache

3.9 out of 5

4 reviews
100% willing to recommend

142 followers

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What is Solr?

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.

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Solr is the #8 ranked solution in top Search as a Service vendors. PeerSpot users give Solr an average rating of 7.8 out of 10. Solr is most commonly compared to Elastic Search: Solr vs Elastic Search. Solr is popular among the large enterprise segment, accounting for 58% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 17% of all views.

Buyer's Guide

Search as a Service

June 2025

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Helped 859,579 peers since 2012

Featured Solr reviews

reviewer1368636

Data Scientist at a comms service provider with 10,001+ employees

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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reviewer823641

Senior Search Engineer at a financial services firm with 51-200 employees

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.

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it_user803529

Senior Software Engineer, Search at a tech services company with 501-1,000 employees

It has improved our search ranking, relevancy, search performance, and user retention Sharding data Faceting Hit Highlighting Parent-child Block Join and Grouping Multi-mode platform SolrCloud stability, indexing and commit speed, and real-time indexing need improvement. Three to five years.…

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Solr mindshare

As of July 2025, the mindshare of Solr in the Search as a Service category stands at 6.4%, up from 6.3% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Search as a Service

Key learnings from peers

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."
"The most valuable feature is the ability to perform a natural language search."
"Sharding data, Faceting, Hit Highlighting, parent-child Block Join and Grouping, and multi-mode platform are all valuable features."

Room for 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."
"The performance for this solution, in terms of queries, could be improved."
"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."