"The best feature is its scalability in that Cloud is always on the fly."
"The quality of the solution is good."
"The solution has good security features. I have been happy with the dashboards and interface."
"It's a stable solution and we have not had any issues."
"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 initial installation and setup were straightforward."
"I like how it allows us to connect to Kafka and get this data in a document format very easily. Elasticsearch is very fast when you do text-based searches of documents. That area is very good, and the search is very good."
"I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly."
"The solution is quite scalable and this is one of its advantages."
"There's lots of processing power. You can actually just add machines to get more performance if you need to. It's pretty flexible and very easy to add another log. It's not like 'oh, no, it's going to be so much extra data'. That's not a problem for the machine. It can handle it."
"The solution should improve the recovery aspects that it has on offer."
"Security is a concern but they're working on it."
"Improving machine learning capabilities would be beneficial."
"I have not been using the solution for many years to know exactly the improvements needed. However, they could simplify how the YML files have to be structured properly."
"It should be easier to use. It has been getting better because many functions are pre-defined, but it still needs improvement."
"The price could be better. Kibana has some limitations in terms of the tablet to view event logs. I also have a high volume of data. On the initialization part, if you chose Kibana, you'll have some limitations. Kibana was primarily proposed as a log data reviewer to build applications to the viewer log data using Kibana. Then it became a virtualization tool, but it still has limitations from a developer's point of view."
"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."
"The reports could improve."
"There are some features lacking in ELK Elasticsearch."
"There is an index issue in which the data starts to crash as it increases."
Earn 20 points
Amazon AWS CloudSearch is ranked 5th in Search as a Service with 2 reviews while ELK Elasticsearch is ranked 1st in Search as a Service with 19 reviews. Amazon AWS CloudSearch is rated 8.6, while ELK Elasticsearch is rated 8.0. The top reviewer of Amazon AWS CloudSearch writes "Good quality and pricing with the capabilities to optimize as needed". On the other hand, the top reviewer of ELK Elasticsearch writes "Good processing power, very scalable, and able to handle all data formats". Amazon AWS CloudSearch is most compared with Amazon Kendra, Amazon Athena, Algolia, Amazon Elasticsearch Service and Azure Search, whereas ELK Elasticsearch is most compared with Amazon Athena, Azure Search, Splunk User Behavior Analytics, Loom Systems and Solr. See our Amazon AWS CloudSearch vs. ELK Elasticsearch report.
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