We performed a comparison between Amazon AWS CloudSearch 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 feature of Amazon AWS CloudSearch is the cloud aspect. I do not need to have the physical infrastructure, everything is in the cloud."
"The most valuable feature of Amazon AWS CloudSearch is its ability to receive data quickly. You can access your data easily in a short time."
"The quality of the solution is good."
"AWS CloudSearch's best features are good performance under high CPU and memory use, and ease of deployment and scaling."
"CDN service reduces latency when accessing our web application."
"It's the best solution for any company. It has a hosting ERP system for any task. AWS is stable. AWS is more flexible and its elastic concept is a new concept. AWS is also very secure. It has many layers of security, like hardware security and software security. This is a big issue."
"Document indexing, text-based search API, and Geospatial searches are all good features."
"It is remarkably efficient and beneficial."
"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."
"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."
"We'd like to see more database features."
"Latlon data type only supports single value per document. All other types support multiple values. We faced issues with this because we had scenarios where, for each document, we needed to store multiple latlon values for different geographical locations."
"AWS CloudSearch's documentation isn't very clear. Also, the on-premise version of the solution is less stable than the cloud version."
"The price of the solution can be expensive."
"Regarding the period of propagation on CDN servers, sometimes we update photos or files and we don't see the update instantly. We need to wait for sometime."
"Security is a concern but they're working on it."
"I would say that it needs to keep its cost competitive in the market, especially in comparison to other clouds."
"A reboot should be enhanced."
"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."
"SolrCloud stability, indexing and commit speed, and real-time Indexing need improvement."
"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."
"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
Amazon AWS CloudSearch is ranked 5th in Search as a Service with 12 reviews while Solr is ranked 8th in Search as a Service. Amazon AWS CloudSearch is rated 8.4, while Solr is rated 7.8. The top reviewer of Amazon AWS CloudSearch writes "A reasonably priced solution that provides scalability, stability, reliability, and security". On the other hand, the top reviewer of Solr writes "Good indexing and decent stability, but requires more documentation". Amazon AWS CloudSearch is most compared with Amazon Kendra, Algolia, Amazon Athena, Elastic Search and Azure Search, whereas Solr is most compared with Amazon Kendra, Elastic Search, Azure Search and Algolia.
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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.