Amazon Kendra vs Elastic Search comparison

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4,027 views|2,940 comparisons
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4,433 views|1,472 comparisons
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Amazon Kendra and Elastic Search based on real PeerSpot user reviews.

Find out what your peers are saying about Elastic, Amazon, Microsoft and others in Search as a Service.
To learn more, read our detailed Search as a Service Report (Updated: March 2024).
765,234 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"Provides flexibility to tune the relevance and ranking of results.""We have good use cases where stability is everything. So it's a stable solution."

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"We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company.""I value the feature that allows me to share the dashboards to different people with different levels of access.""The most valuable feature of Elastic Enterprise Search is user behavior analysis.""The initial setup is very easy for small environments.""The most valuable features are its user-friendly interface and seamless navigation.""The initial installation and setup were straightforward.""The most valuable feature of Elastic Enterprise Search is the Discovery option for the visualization of logs on a GPU instead of on the server.""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."

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Cons
"There are some token limits.""The time it takes for indexing documents could be reduced."

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"It was not possible to use authentication three years back. You needed to buy the product's services for authentication.""The UI point of view is not very powerful because it is dependent on Kibana.""Something that could be improved is better integrations with Cortex and QRadar, for example.""The pricing of this product needs to be more clear because I cannot understand it when I review the website.""Performance improvement could come from skipping background refresh on search idle shards (which is already being addressed in the upcoming seventh version).""Dashboards could be more flexible, and it would be nice to provide more drill-down capabilities.""This product could be improved with additional security, and the addition of support for machine learning devices.""They should improve its documentation. Their official documentation is not very informative. They can also improve their technical support. They don't help you much with the customized stuff. They also need to add more visuals. Currently, they have line charts, bar charts, and things like that, and they can add more types of visuals. They should also improve the alerts. They are not very simple to use and are a bit complex. They could add more options to the alerting system."

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Pricing and Cost Advice
  • "The pricing falls in the medium range."
  • More Amazon Kendra Pricing and Cost Advice →

  • "ELK has been considered as an alternative to Splunk to reduce licensing costs."
  • "An X-Pack license is more affordable than Splunk."
  • "​The pricing and license model are clear: node-based model."
  • "This is a free, open source software (FOSS) tool, which means no cost on the front-end. There are no free lunches in this world though. Technical skill to implement and support are costly on the back-end with ELK, whether you train/hire internally or go for premium services from Elastic."
  • "We are using the free version and intend to upgrade."
  • "It can be expensive."
  • "This product is open-source and can be used free of charge."
  • "We are using the open-sourced version."
  • More Elastic Search Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:We have good use cases where stability is everything. So it's a stable solution.
    Top Answer:The pricing falls in the medium range. The cost depends on the size of your use case because it has a fixed cost, not a variable. The licensing is on a monthly basis. There are no extra costs. Only… more »
    Top Answer:There are some token limits. We cannot ask questions with more than 30 tokens. Access cannot be more than 200 tokens. And the token is also, like, one point. Then views are very hard limits, and it is… more »
    Top Answer:Data indexing of historical data is the most beneficial feature of the product.
    Top Answer:I use the community version. The premium license is expensive. I rate the tool’s pricing an eight out of ten.
    Top Answer:The solution must provide AI integrations. I could direct my data flow to my AI tools if I use Elastic for IoT data.
    Ranking
    2nd
    out of 12 in Search as a Service
    Views
    4,027
    Comparisons
    2,940
    Reviews
    1
    Average Words per Review
    740
    Rating
    8.0
    1st
    out of 12 in Search as a Service
    Views
    4,433
    Comparisons
    1,472
    Reviews
    27
    Average Words per Review
    512
    Rating
    8.3
    Comparisons
    Also Known As
    Elastic Enterprise Search, Swiftype, Elastic Cloud
    Learn More
    Overview

    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.

    Elasticsearch is a prominent open-source search and analytics engine known for its scalability, reliability, and straightforward management. It's a favored choice among enterprises for real-time data search, analysis, and visualization. Open-source Elasticsearch is free, offering a comprehensive feature set and scalability. It allows full control over deployments but requires managing and maintaining the infrastructure. On the other hand, Elastic Cloud provides a managed service with features like automated provisioning, high availability, security, and global reach.

    Elasticsearch excels in handling time-sensitive data and complex search requirements across large datasets. Its scalability allows it to handle growing data volumes efficiently, maintaining high performance and fast response times. Integrated with Kibana, Elasticsearch enables powerful data visualization, providing real-time insights crucial for data-driven decision-making.

    Elastic Cloud reduces operational overhead and improves scalability and performance, though it comes with associated costs. It is available on your preferred cloud provider — AWS, Azure, or Google Cloud. Customers who want to manage the software themselves, whether on public, private, or hybrid cloud, can download the Elastic Stack.

    At its core, Elasticsearch is renowned for its full-text search capabilities, capable of performing complex queries and supporting features like fuzzy matching and auto-complete.

    Peer reviews from various professionals highlight its strengths and weaknesses. Pros include its detection and correlation features, flexibility, cloud-readiness, extensibility, and efficient search capabilities. However, users have noted challenges like steep learning curves, data analysis limitations, and integration complexities. The platform is generally viewed as stable and scalable, with varying degrees of satisfaction regarding its usability and feature set.

    In summary, Elasticsearch stands out for its high-speed search, scalability, and versatile analytics, making it a go-to solution for organizations managing large datasets. Its adaptability to different enterprise needs, robust community support, and continuous development keep it at the forefront of enterprise search and analytics solutions. However, potential users should be aware of its learning curve and the need for skilled personnel for optimization.

    Sample Customers
    Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
    T-Mobile, Adobe, Booking.com, BMW, Telegraph Media Group, Cisco, Karbon, Deezer, NORBr, Labelbox, Fingerprint, Relativity, NHS Hospital, Met Office, Proximus, Go1, Mentat, Bluestone Analytics, Humanz, Hutch, Auchan, Sitecore, Linklaters, Socren, Infotrack, Pfizer, Engadget, Airbus, Grab, Vimeo, Ticketmaster, Asana, Twilio, Blizzard, Comcast, RWE and many others.
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm21%
    Computer Software Company15%
    Manufacturing Company8%
    Government7%
    REVIEWERS
    Financial Services Firm33%
    Computer Software Company27%
    Manufacturing Company10%
    Insurance Company7%
    VISITORS READING REVIEWS
    Computer Software Company18%
    Financial Services Firm15%
    Government8%
    Manufacturing Company7%
    Company Size
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise12%
    Large Enterprise70%
    REVIEWERS
    Small Business41%
    Midsize Enterprise11%
    Large Enterprise48%
    VISITORS READING REVIEWS
    Small Business23%
    Midsize Enterprise13%
    Large Enterprise63%
    Buyer's Guide
    Search as a Service
    March 2024
    Find out what your peers are saying about Elastic, Amazon, Microsoft and others in Search as a Service. Updated: March 2024.
    765,234 professionals have used our research since 2012.

    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, Solr and Algolia, whereas Elastic Search is most compared with Milvus, Faiss, Azure Search, Pinecone and OpenText IDOL.

    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.