Amazon Elasticsearch Service vs Elastic Search comparison

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Executive Summary

We performed a comparison between Amazon Elasticsearch Service 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 Elasticsearch Service 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
"In case there is a failure, Elastic manages everything well, and there no major downtime.""They have the good documentation in the help text and that is the reason the Amazon is the perfect solution in the current market.""The initial set up is very easy...We really appreciate Amazon!""The stability of the product is good.""Regarding valuable features of the solution, we found with the process, which we have used in both cases where we used the solution that while you're seeing the streaming of data, you can analyze in the initial phase what sort of data you are streaming and whether it is valuable.""The most valuable features of Amazon Elasticsearch are ease of use, native JSON, and efficiency. Additionally, handles many use cases and search grammar was useful.""It enables us to efficiently search and retrieve our event data, offering us a versatile approach to locate specific information within these logs.""It's a good log management platform. In terms of infrastructure management, it's good."

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"I value the feature that allows me to share the dashboards to different people with different levels of access.""The most valuable feature is the out of the box Kibana.""It is easy to scale with the cluster node model.​""Data indexing of historical data is the most beneficial feature of the product.""It gives us the possibility to store and query this data and also do this efficiently and securely and without delays.""The most valuable features are the detection and correlation features.""The solution has good security features. I have been happy with the dashboards and interface.""The solution offers good stability."

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Cons
"Amazon Elasticsearch can improve the bullion in the near search and the ease of integration with Kibana. Additionally, there could be more flexibility in the configuration and documentation.""There is a problem with the database. Amazon only provides the hosting to run our applications bias, but there is no option to manage the database within the Elasticsearch product.""One glaring issue was with our mapping configuration as the system accepted the data we posted, but after a few months, when we attempted complex queries, we realized the date formatting had become problematic.""The configuration should be more straightforward because we had to select a lot of things.""I want to see a new feature in Amazon Elasticsearch Service that allows users to create default filters for filtered levels.""I would say that, basically, the configuration part is an area with a shortcoming...Some upgradation is required on the configuration side so that we can get to use it."

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"Improving machine learning capabilities would be beneficial.""I would like to see more integration for the solution with different platforms.""I would like to be able to do correlations between multiple indexes.""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.""There are potential improvements based on our client feedback, like unifying the licensing cost structure.""Better dashboards or a better configuration system would be very good.""They're making changes in their architecture too frequently.""Performance improvement could come from skipping background refresh on search idle shards (which is already being addressed in the upcoming seventh version)."

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Pricing and Cost Advice
  • "You only pay for what you use."
  • "Compared to other cloud platforms, it is manageable and not very expensive."
  • "There is a community edition available and the price of the commercial offering is reasonable."
  • "The solution is not expensive, but priced averagely, I will say."
  • More Amazon Elasticsearch Service 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:It enables us to efficiently search and retrieve our event data, offering us a versatile approach to locate specific information within these logs.
    Top Answer:The solution is not expensive, but priced averagely, I will say. Regarding the pricing part based on the use cases, we used to sometimes see or do some of the costing parts also in that case… more »
    Top Answer:One glaring issue was with our mapping configuration as the system accepted the data we posted, but after a few months, when we attempted complex queries, we realized the date formatting had become… 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
    3rd
    out of 12 in Search as a Service
    Views
    3,171
    Comparisons
    2,725
    Reviews
    4
    Average Words per Review
    616
    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 Elasticsearch Service is a managed service that makes it easy to deploy, operate, and scale Elasticsearch clusters in the AWS Cloud.

    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
    VIDCOIN, Wyng, Yellow New Zealand, zipMoney, Cimri, Siemens, Unbabel
    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 Firm20%
    Computer Software Company14%
    Manufacturing Company9%
    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 Business15%
    Midsize Enterprise13%
    Large Enterprise72%
    REVIEWERS
    Small Business41%
    Midsize Enterprise11%
    Large Enterprise48%
    VISITORS READING REVIEWS
    Small Business23%
    Midsize Enterprise13%
    Large Enterprise63%
    Buyer's Guide
    Amazon Elasticsearch Service vs. Elastic Search
    March 2024
    Find out what your peers are saying about Amazon Elasticsearch Service vs. Elastic Search and other solutions. Updated: March 2024.
    765,386 professionals have used our research since 2012.

    Amazon Elasticsearch Service is ranked 3rd in Search as a Service with 6 reviews while Elastic Search is ranked 1st in Search as a Service with 59 reviews. Amazon Elasticsearch Service is rated 8.2, while Elastic Search is rated 8.2. The top reviewer of Amazon Elasticsearch Service writes "Easy to use, efficient, and straightforward installation". On the other hand, the top reviewer of Elastic Search writes "Played a crucial role in enhancing our cybersecurity efforts ". Amazon Elasticsearch Service is most compared with Amazon Athena, Amazon Kendra and Amazon AWS CloudSearch, whereas Elastic Search is most compared with Milvus, Faiss, Azure Search, Amazon Kendra and Exalead. See our Amazon Elasticsearch Service 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.