Amazon Athena vs Elastic Search comparison

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2,318 views|2,093 comparisons
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4,433 views|1,472 comparisons
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).
765,386 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
"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.""The solution is very easy to use and integrations are very smooth.""You can perform SQL queries in S3 using Athena.""Amazon Athena is very stable. I never had any issues with it. The dashboarding tool is okay.""Athena has a really good UI and is very compatible with on-prem products.""It's easy to set up the product."

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"It helps us to analyse the logs based on the location, user, and other log parameters.""The most valuable feature of Elastic Enterprise Search is user behavior analysis.""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 setup is very easy for small environments.""The initial installation and setup were straightforward.""It's a stable solution and we have not had any issues.""The most valuable features of Elastic Enterprise Search are it's cloud-ready and we do a lot of infrastructure as code. By using ELK, we're able to deploy the solution as part of our ISC deployment.""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."

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Cons
"You have to build out the metadata yourself because of the nature of the cloud.""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.""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.""I would like to use Spark or Python-based queries in Athena.""The solution should include a better API for query services."

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"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.""The metadata gets stored along with indexes and isn't queryable.""While integrating with tools like agents for ingesting data from sources like firewalls is valuable, I believe prioritizing improvements to the core product would be more beneficial.""The UI point of view is not very powerful because it is dependent on Kibana.""Improving machine learning capabilities would be beneficial.""There are some features lacking in ELK Elasticsearch.""Machine learning on search needs improvement.""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 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: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
    4th
    out of 12 in Search as a Service
    Views
    2,318
    Comparisons
    2,093
    Reviews
    6
    Average Words per Review
    377
    Rating
    7.7
    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 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 Company17%
    Manufacturing Company8%
    Government8%
    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 Business17%
    Midsize Enterprise12%
    Large Enterprise71%
    REVIEWERS
    Small Business41%
    Midsize Enterprise11%
    Large Enterprise48%
    VISITORS READING REVIEWS
    Small Business23%
    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.
    765,386 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 Milvus, Faiss, Azure Search, Amazon Kendra 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.