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 data store and the X-pack extension."
"A nonstructured database that can manage large amounts of nonstructured data."
"The most valuable features of Elastic Enterprise Search are it's cloud-ready and we do a lot of infrastructure as code. By using ELK, we're able to deploy the solution as part of our ISC deployment."
"The most valuable features are the detection and correlation features."
"The solution has great scalability."
"The flexibility and the support for diverse languages that it provides for searching the database are most valuable. We can use different languages to query the database."
"The ability to aggregate log and machine data into a searchable index reduces time to identify and isolate issues for an application. Saves time in triage and incident response by eliminating manual steps to access and parse logs on separate systems, within large infrastructure footprints."
"The observability is the best available because it provides granular insights that identify reasons for defects."
"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."
"Sharding data, Faceting, Hit Highlighting, parent-child Block Join and Grouping, and multi-mode platform are all valuable features."
"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."
"There are a lot of manual steps on the operating system. It could be simplified in the user interface."
"There are some features lacking in ELK Elasticsearch."
"There is a lack of technical people to develop, implement and optimize equipment operation and web queries."
"Elastic Search needs to improve authentication. It also needs to work on the Kibana visualization dashboard."
"They could improve some of the platform's infrastructure management capabilities."
"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."
"This product could be improved with additional security, and the addition of support for machine learning devices."
"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."
"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."
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.
