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."The most valuable features are the detection and correlation features."
"You have dashboards, it is visual, there are maps, you can create canvases. It's more visual than anything that I've ever used."
"There's lots of processing power. You can actually just add machines to get more performance if you need to. It's pretty flexible and very easy to add another log. It's not like 'oh, no, it's going to be so much extra data'. That's not a problem for the machine. It can handle it."
"ELK Elasticsearch is 100% scalable as scalability is built into the design"
"The solution has great scalability."
"The solution offers good stability."
"X-Pack provides good features, like authorization and alerts."
"The initial setup is very easy for small environments."
"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."
"Both the graph feature and the reporting feature are a little bit lacking. The alerting also needs to be improved."
"Better dashboards or a better configuration system would be very good."
"It is hard to learn and understand because it is a very big platform. This is the main reason why we still have nothing in production. We have to learn some things before we get there."
"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."
"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."
"Improving machine learning capabilities would be beneficial."
"They're making changes in their architecture too frequently."
"Machine learning on search needs improvement."
"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."
"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."
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.
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