Compare Amazon Elasticsearch Service vs. Amazon Kendra

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Find out what your peers are saying about Elastic, Microsoft, Amazon and others in Search as a Service. Updated: November 2020.
448,775 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"In case there is a failure, Elastic manages everything well, and there no major downtime."

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"Provides flexibility to tune the relevance and ranking of results."

More Amazon Kendra Pros »

Cons
"The configuration should be more straightforward because we had to select a lot of things."

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"The time it takes for indexing documents could be reduced."

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Pricing and Cost Advice
"Compared to other cloud platforms, it is manageable and not very expensive."

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448,775 professionals have used our research since 2012.
Ranking
5th
out of 11 in Search as a Service
Views
1,476
Comparisons
1,028
Reviews
1
Average Words per Review
422
Avg. Rating
8.0
6th
out of 11 in Search as a Service
Views
1,155
Comparisons
1,032
Reviews
1
Average Words per Review
451
Avg. Rating
7.0
Popular Comparisons
Compared 10% of the time.
Compared 5% of the time.
Compared 2% of the time.
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Amazon
Amazon
Overview

Amazon Elasticsearch Service is a managed service that makes it easy to deploy, operate, and scale Elasticsearch clusters in the AWS Cloud.

Amazon Kendra is a highly accurate and easy to use enterprise search service that’s powered by machine learning. Kendra enables developers to add search capabilities to their applications so their end users can discover information stored within the vast amount of content spread across their company. This includes data from manuals, research reports, FAQs, HR documentation, customer service guides, and is found across various systems such as file systems, web sites, Box, DropBox, Salesforce, SharePoint, relational databases, Amazon S3, and more. When you type a question, the service uses machine learning algorithms to understand the context and return the most relevant results, whether that be a precise answer or an entire document. For example, you can ask a question like "How much is the cash reward on the corporate credit card?” and Kendra will map to the relevant documents and return a specific answer like “2%”. Kendra provides sample code so that you can get started quickly and easily integrate highly accurate search into your new or existing applications.

Offer
Learn more about Amazon Elasticsearch Service
Learn more about Amazon Kendra
Sample Customers
VIDCOIN, Wyng, Yellow New Zealand, zipMoney, Cimri, Siemens, UnbabelExpedia, Intuit, Royal Dutch Shell, Brooks Brothers
Top Industries
VISITORS READING REVIEWS
Media Company46%
Computer Software Company22%
Comms Service Provider10%
Financial Services Firm4%
VISITORS READING REVIEWS
Media Company43%
Computer Software Company23%
Comms Service Provider8%
K 12 Educational Company Or School4%
Find out what your peers are saying about Elastic, Microsoft, Amazon and others in Search as a Service. Updated: November 2020.
448,775 professionals have used our research since 2012.

Amazon Elasticsearch Service is ranked 5th in Search as a Service with 1 review while Amazon Kendra is ranked 6th in Search as a Service with 1 review. Amazon Elasticsearch Service is rated 8.0, while Amazon Kendra is rated 7.0. The top reviewer of Amazon Elasticsearch Service writes "Timely support, recovers easily from failure, and in general it makes our lives easy". On the other hand, the top reviewer of Amazon Kendra writes "Tunes the relevance and ranking of results which improves accuracy; price is very high". Amazon Elasticsearch Service is most compared with Amazon AWS CloudSearch, Amazon Athena and Algolia, whereas Amazon Kendra is most compared with Amazon AWS CloudSearch, Azure Search, Solr 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.