Amazon Athena vs Elastic Search comparison

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Amazon Web Services (AWS) Logo
2,284 views|2,060 comparisons
83% willing to recommend
Elastic Logo
3,993 views|1,325 comparisons
98% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Amazon Athena 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.
To learn more, read our detailed Amazon Athena vs. Elastic Search Report (Updated: March 2024).
768,857 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
"It's easy to set up the product.""The solution is very easy to use and integrations are very smooth.""One of the most valuable features is the ability to partition your databases. I also like the federal query functionality, for cases when you have to query outside your S3 storage, or even completely outside of the AWS platform.""Amazon Athena is very stable. I never had any issues with it. The dashboarding tool is okay.""You can perform SQL queries in S3 using Athena.""Athena has a really good UI and is very compatible with on-prem products."

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"The solution has good security features. I have been happy with the dashboards and interface.""The solution offers good stability.""The most valuable feature of the solution is its utility and usefulness.""The tool's stability and performance are good.""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.""The initial installation and setup were straightforward.""Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time analytics with Elastic benefits us due to the huge traffic volume in our organization, which reaches up to 60,000 requests per second. With logs of approximately 25 GB per day, manually analyzing traffic behavior, payloads, headers, user agents, and other details is impractical.""A good use case is saving metadata of your systems for data cataloging. Various systems, like those opened in metadata and similar applications, use Elasticsearch to store their text data."

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Cons
"The solution should include a better API for query services.""I would like to use Spark or Python-based queries in Athena.""One improvement I can suggest is that Athena needs to work better with third-parties. For example, the process of querying a Microsoft SQL warehouse could be improved.""You have to build out the metadata yourself because of the nature of the cloud.""If you compare it with Palantir, if you have some data and you want to quickly have a look at it, then that feature is not available in Amazon Cloud.""I think it would be better if the product were more mature. It's still a young product compared to Power BI or Qlik. I find that development is a bit difficult, but it might be because I'm used to other tools. The dashboarding capabilities could be better. The reporting and statement generation could be better. I couldn't technically initiate picture-perfect reporting, for example, to send out statements every month for banking customers."

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"The solution must provide AI integrations.""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.""There are a lot of manual steps on the operating system. It could be simplified in the user interface.""The metadata gets stored along with indexes and isn't queryable.""The solution's integration and configuration are not easy. Not many people know exactly what to do.""Elastic Search needs to improve authentication. It also needs to work on the Kibana visualization dashboard.""It was not possible to use authentication three years back. You needed to buy the product's services for authentication.""Could have more open source tools and testing."

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Pricing and Cost Advice
  • "The solution operates on a serverless model so you only pay for data that you consume."
  • "I am happy with what they are charging and how they charge it, especially because they charge you per query, and not per series."
  • "It doesn't cost much if you are already part of the AWS ecosystem."
  • "Athena is very inexpensive for being a cloud tool."
  • More Amazon Athena 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:Athena has a really good UI and is very compatible with on-prem products.
    Top Answer:You have to build out the metadata yourself because of the nature of the cloud.
    Top Answer:Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time… more »
    Top Answer:I don't see improvements at the moment. The current setup is working well for me, and I'm satisfied with it. Integrating with different platforms is also fine, and I'm not recommending any changes or… more »
    Ranking
    4th
    out of 13 in Search as a Service
    Views
    2,284
    Comparisons
    2,060
    Reviews
    6
    Average Words per Review
    377
    Rating
    7.7
    1st
    out of 13 in Search as a Service
    Views
    3,993
    Comparisons
    1,325
    Reviews
    27
    Average Words per Review
    501
    Rating
    8.3
    Comparisons
    Also Known As
    Elastic Enterprise Search, Swiftype, Elastic Cloud
    Learn More
    Overview

    Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

    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
    bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
    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 Firm19%
    Computer Software Company18%
    Manufacturing Company8%
    Government8%
    REVIEWERS
    Financial Services Firm33%
    Computer Software Company27%
    Manufacturing Company10%
    Insurance Company7%
    VISITORS READING REVIEWS
    Computer Software Company18%
    Financial Services Firm15%
    Government7%
    Manufacturing Company7%
    Company Size
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise13%
    Large Enterprise71%
    REVIEWERS
    Small Business41%
    Midsize Enterprise11%
    Large Enterprise48%
    VISITORS READING REVIEWS
    Small Business24%
    Midsize Enterprise13%
    Large Enterprise63%
    Buyer's Guide
    Amazon Athena vs. Elastic Search
    March 2024
    Find out what your peers are saying about Amazon Athena vs. Elastic Search and other solutions. Updated: March 2024.
    768,857 professionals have used our research since 2012.

    Amazon Athena is ranked 4th in Search as a Service with 6 reviews while Elastic Search is ranked 1st in Search as a Service with 59 reviews. Amazon Athena is rated 7.6, while Elastic Search is rated 8.2. The top reviewer of Amazon Athena writes "A great AWS application that is easy to set up and simple to expand". On the other hand, the top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". Amazon Athena is most compared with Amazon Elasticsearch Service, Amazon AWS CloudSearch, Azure Search and Solr, whereas Elastic Search is most compared with Faiss, Milvus, Azure Search and Pinecone. See our Amazon Athena 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.