We performed a comparison between Elastic Search and Solr based on real PeerSpot user reviews.
Find out what your peers are saying about Elastic, Amazon Web Services (AWS), Microsoft and others in Search as a Service."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."
"The most valuable feature is the out of the box Kibana."
"The solution has good security features. I have been happy with the dashboards and interface."
"It gives us the possibility to store and query this data and also do this efficiently and securely and without delays."
"The most valuable feature of Elastic Enterprise Search is user behavior analysis."
"I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly."
"The UI is very nice, and performance wise it's quite good too."
"We can easily collect all the data and view historical trends using the product. We can view the applications and identify the issues effectively."
"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."
"The one area that can use improvement is the automapping of fields."
"There is an index issue in which the data starts to crash as it increases."
"I would like to see more integration for the solution with different platforms."
"Dashboards could be more flexible, and it would be nice to provide more drill-down capabilities."
"There is a lack of technical people to develop, implement and optimize equipment operation and web queries."
"We see the need for some improvements with Elasticsearch. We would like the Elasticsearch package to include training lessons for our staff."
"Elastic Search needs to improve its technical support. It should be customer-friendly and have good support."
"They should improve its documentation. Their official documentation is not very informative. They can also improve their technical support. They don't help you much with the customized stuff. They also need to add more visuals. Currently, they have line charts, bar charts, and things like that, and they can add more types of visuals. They should also improve the alerts. They are not very simple to use and are a bit complex. They could add more options to the alerting system."
"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."
"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."
"SolrCloud stability, indexing and commit speed, and real-time Indexing need improvement."
Earn 20 points
Elastic Search is ranked 1st in Search as a Service with 59 reviews while Solr is ranked 8th in Search as a Service. Elastic Search is rated 8.2, while Solr is rated 7.8. The top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". On the other hand, the top reviewer of Solr writes "Good indexing and decent stability, but requires more documentation". Elastic Search is most compared with Faiss, Milvus, Azure Search, Pinecone and Amazon Kendra, whereas Solr is most compared with Amazon AWS CloudSearch, Amazon Kendra, Azure Search, Algolia and Amazon Athena.
See our list of best Search as a Service vendors.
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.
