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, Microsoft and others in Search as a Service."The most valuable features are the ease and speed of the setup."
"We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company."
"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."
"The UI is very nice, and performance wise it's quite good too."
"The observability is the best available because it provides granular insights that identify reasons for defects."
"It is stable."
"The most valuable feature of the solution is its utility and usefulness."
"The most valuable features are the data store and the X-pack extension."
"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."
"It should be easier to use. It has been getting better because many functions are pre-defined, but it still needs improvement."
"Elastic Enterprise Search could improve its SSL integration easier. We should not need to go to the back-end servers to do configuration, we should be able to do it on the GUI."
"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 different applications need to be individually deployed."
"Elastic Search could benefit from a more user-friendly onboarding process for beginners."
"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 Search needs to improve its technical support. It should be customer-friendly and have good support."
"The pricing of this product needs to be more clear because I cannot understand it when I review the website."
"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."
"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."
"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."
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 Milvus, Faiss, Azure Search 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.