We performed a comparison between Elastic Search and Solr based on real PeerSpot user reviews.
Find out in this report how the two Search as a Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The most valuable feature of Elastic Enterprise Search is the opportunity to search behind and between different logs."
"The product is scalable with good performance."
"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 initial setup is very easy for small environments."
"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."
"The solution has great scalability."
"Data indexing of historical data is the most beneficial feature of the product."
"The products comes with REST APIs."
"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."
"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."
"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."
"They could improve some of the platform's infrastructure management capabilities."
"They're making changes in their architecture too frequently."
"Elastic Enterprise Search could improve the report templates."
"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."
"While integrating with tools like agents for ingesting data from sources like firewalls is valuable, I believe prioritizing improvements to the core product would be more beneficial."
"Something that could be improved is better integrations with Cortex and QRadar, for example."
"Elastic Search could benefit from a more user-friendly onboarding process for beginners."
"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."
"SolrCloud stability, indexing and commit speed, and real-time Indexing need improvement."
"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, Pinecone, Azure Search and Amazon Kendra, whereas Solr is most compared with Amazon AWS CloudSearch, Amazon Kendra, Azure Search and Algolia. See our Elastic Search vs. Solr report.
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.
