We performed a comparison between Amazon Kendra and Elastic Search based on real PeerSpot user reviews.
Find out in this report how the two Search as a Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."We have good use cases where stability is everything. So it's a stable solution."
"Provides flexibility to tune the relevance and ranking of results."
"The most valuable feature is the out of the box Kibana."
"Search is really powerful."
"The solution is stable and reliable."
"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."
"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 most valuable feature of the solution is its utility and usefulness."
"Implementing the main requirements regarding my support portal."
"I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly."
"There are some token limits."
"The time it takes for indexing documents could be reduced."
"The solution must provide AI integrations."
"It is hard to learn and understand because it is a very big platform. This is the main reason why we still have nothing in production. We have to learn some things before we get there."
"Elasticsearch could improve by honoring Unix environmental variables and not relying only on those provided by Java (e.g. installing plugins over the Unix http proxy)."
"Its licensing needs to be improved. They don't offer a perpetual license. They want to know how many nodes you will be using, and they ask for an annual subscription. Otherwise, they don't give you permission to use it. Our customers are generally military or police departments or customers without connection to the internet. Therefore, this model is not suitable for us. This subscription-based model is not the best for OEM vendors. Another annoying thing about Elasticsearch is its roadmap. We are developing something, and then they say, "Okay. We have removed that feature in this release," and when we are adapting to that release, they say, "Okay. We have removed that one as well." We don't know what they will remove in the next version. They are not looking for backward compatibility from the customers' perspective. They just remove a feature and say, "Okay. We've removed this one." In terms of new features, it should have an ODBC driver so that you can search and integrate this product with existing BI tools and reporting tools. Currently, you need to go for third parties, such as CData, in order to achieve this. ODBC driver is the most important feature required. Its Community Edition does not have security features. For example, you cannot authenticate with a username and password. It should have security features. They might have put it in the latest release."
"I would rate the stability a seven out of ten. We faced a few issues."
"Machine learning on search needs improvement."
"Enterprise scaling of what have been essentially separate, free open source software (FOSS) products has been a challenge, but the folks at Elastic have published new add-ons (X-Pack and ECE) to help large companies grow ELK to required scales."
"The documentation regarding customization could be better."
Amazon Kendra is ranked 2nd in Search as a Service with 2 reviews while Elastic Search is ranked 1st in Search as a Service with 59 reviews. Amazon Kendra is rated 7.6, while Elastic Search is rated 8.2. The top reviewer of Amazon Kendra writes "Kendra has a nice AI built-in, enhancing the search experience and highly stable solution". On the other hand, the top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". Amazon Kendra is most compared with Azure Search, Amazon Elasticsearch Service, Amazon AWS CloudSearch, Algolia and Solr, whereas Elastic Search is most compared with Faiss, Milvus, Pinecone, Azure Search and Qdrant. See our Amazon Kendra vs. Elastic Search report.
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.
