We performed a comparison between Algolia, 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 Algolia solution really helped us to improve our conversion rate and click through rate."
"It will remain alive in the market. The solution will be stable in the market."
"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."
"Document indexing, text-based search API, and Geospatial searches are all good features."
"The initial setup is straightforward."
"The quality of the solution is good."
"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."
"AWS CloudSearch's best features are good performance under high CPU and memory use, and ease of deployment and scaling."
"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."
"Sharding data, Faceting, Hit Highlighting, parent-child Block Join and Grouping, and multi-mode platform are all valuable features."
"It has improved our search ranking, relevancy, search performance, and user retention."
"I think they could improve the analytics view."
"AWS CloudSearch's documentation isn't very clear. Also, the on-premise version of the solution is less stable than the cloud version."
"Maybe they are common in Egypt, but you should make a request on Amazon to create a function to monitor CPU performance, memory, and files. It is very difficult in AWS. I would tell them it should be simple, just drag and drop. I think they could develop this option so we can drag and drop to monitor performance of the processor and memory."
"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."
"We'd like to see more database features."
"Security is a concern but they're working on it."
"The solution should improve the recovery aspects that it has on offer."
"Amazon AWS CloudSearch is highly stable. However, the speed depends on your internet connection."
"The price of the solution can be expensive."
"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."
"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."
Earn 20 points
