We performed a comparison between Amazon Elasticsearch Service 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 of Amazon Elasticsearch are ease of use, native JSON, and efficiency. Additionally, handles many use cases and search grammar was useful."
"The initial set up is very easy...We really appreciate Amazon!"
"They have the good documentation in the help text and that is the reason the Amazon is the perfect solution in the current market."
"The stability of the product is good."
"It enables us to efficiently search and retrieve our event data, offering us a versatile approach to locate specific information within these logs."
"Regarding valuable features of the solution, we found with the process, which we have used in both cases where we used the solution that while you're seeing the streaming of data, you can analyze in the initial phase what sort of data you are streaming and whether it is valuable."
"It's a good log management platform. In terms of infrastructure management, it's good."
"In case there is a failure, Elastic manages everything well, and there no major downtime."
"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."
"The most valuable feature is the ability to perform a natural language search."
"Sharding data, Faceting, Hit Highlighting, parent-child Block Join and Grouping, and multi-mode platform are all valuable features."
"There is a problem with the database. Amazon only provides the hosting to run our applications bias, but there is no option to manage the database within the Elasticsearch product."
"The configuration should be more straightforward because we had to select a lot of things."
"One glaring issue was with our mapping configuration as the system accepted the data we posted, but after a few months, when we attempted complex queries, we realized the date formatting had become problematic."
"I would say that, basically, the configuration part is an area with a shortcoming...Some upgradation is required on the configuration side so that we can get to use it."
"I want to see a new feature in Amazon Elasticsearch Service that allows users to create default filters for filtered levels."
"Amazon Elasticsearch can improve the bullion in the near search and the ease of integration with Kibana. Additionally, there could be more flexibility in the configuration and documentation."
"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
Amazon Elasticsearch Service is ranked 3rd in Search as a Service with 6 reviews while Solr is ranked 8th in Search as a Service. Amazon Elasticsearch Service is rated 8.2, while Solr is rated 7.8. The top reviewer of Amazon Elasticsearch Service writes "Easy to use, efficient, and straightforward installation". On the other hand, the top reviewer of Solr writes "Good indexing and decent stability, but requires more documentation". Amazon Elasticsearch Service is most compared with Amazon Athena, Amazon Kendra, Elastic Search and Amazon AWS CloudSearch, whereas Solr is most compared with Amazon AWS CloudSearch, Amazon Kendra, Elastic Search, Azure Search and Algolia.
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.
