DNIF HYPERCLOUD vs Elastic Beats comparison

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777 views|466 comparisons
85% willing to recommend
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views| comparisons
75% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between DNIF HYPERCLOUD and Elastic Beats based on real PeerSpot user reviews.

Find out what your peers are saying about Splunk, Datadog, Wazuh and others in Log Management.
To learn more, read our detailed Log Management Report (Updated: April 2024).
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Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The dashboard is helpful, and it creates visualizations to let staff review event data and identify patterns and anomalies.""I like the MITRE table, a feature I saw for the first time in the same solution. There was one MITRE tactic table, which can be used to identify threats if you have all kinds of rules enabled or if you have rules for all the tactics in the MITRE table. There are 14 tables in MITRE, and those 14 tables consist of multiple columns, tactics, and techniques. It was one of the first SIEM tools I saw that had that particular MITRE table. On that basis, you can create new rules and identify existing ones. At any point, if an alert is triggered, it will try to match it to any of those MITRE tactics. I liked that creating a workbook on MITRE business was straightforward. I also like that you can search using SQL or DQL.""The solution is quite stable and offers good performance. It also works on a virtual machine. We haven't found any issues with it so far. It's been reliable.""The User Behavior Analytics is a built-in threat-hunting feature. It detects and reports on any kind of malware or ransomware that enters the network.""The response time on queries is super-fast.""The beauty of the solution is that you can develop infrastructure for a data lake using open sources that are separate from the licenses.""Has a great search capability.""Great for scaling productivity for log monitoring purposes."

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"There's a whole spectrum of features on the solution that users can take advantage of. It's a very robust product.""The security aspects in general have been very useful to use."

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Cons
"The solution should be able to connect to endpoints, such as desktops and laptops... If this solution had a smart connector to these logs- Windows, Linux, or any other logs - without affecting the performance of the connector, that would be wonderful.""The vendor is fairly new and it's not as big as some of the international competitors. It's not a mature product. If you ask them to move data, it might take a lot of time.""Dependency on the DNIF support team was frustrating.""There are currently some issues with machine learning plug-ins.""The EBA could be improved.""The solution's command line should be simpler so that routine commands can be used.""I think DNIF HYPERCLOUD can implement the ability to export more than 100,000. At the moment, we can't go beyond that. So many times, if you're checking for the firewall logs and working on something related to authentication or network-related traffic, while that log count is low, the account goes beyond that. You can't restrict the logs or the amount of data you can export. It's very important for my situation. It would be better if they could increase the capacity of exports. Although there are many more types of searching in DNIF HYPERCLOUD, people still struggle to query out what they want because not everyone is good at SQL or DQL. The easiest way to query out in DNIF is using the GUI-based interface. But in the GUI interface, you can use operator calls. It gets tricky when you want to search for a specific type of event. You don't know where it will be passed and whether it will be consistent. In the initial phase, it's tough for us to use DNIF. You cannot pass every event in a stable DNIF. When we used that particular tool, we used to get those logs, but sometimes many things are not getting passed. So, we used to export the sheet or export the data into Excel and weigh the required details. In the next release, I would like them to improve the export of the columns and make the application more user-friendly. I would also like a threat-hunting feature in the next release."

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"The dashboard is not user-friendly. The solution, in general, isn't great from a user's perspective.""At some level, the documentation, the information as far as the components, it's sometimes a little difficult to find the information necessary to implement aspects."

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Pricing and Cost Advice
  • "The pricing is based on the log size."
  • "The solution requires a huge infrastructure and that is costly."
  • More DNIF HYPERCLOUD Pricing and Cost Advice →

  • "It wasn't cheap, but it was cost-effective compared to many of the other solutions."
  • More Elastic Beats Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:The dashboard is helpful, and it creates visualizations to let staff review event data and identify patterns and anomalies.
    Top Answer:The EBA could be improved. The graphs and kill chain are not operational most of the time. Some dashboards are not showing data that is important to have for management review or meetings. The… more »
    Top Answer:In our project, we are mostly using authentication activities, real-time notification & alerting, log correlation & threat intelligence solutions. The DNIF tool is very authentic and capable of… more »
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    Ranking
    24th
    out of 95 in Log Management
    Views
    777
    Comparisons
    466
    Reviews
    5
    Average Words per Review
    774
    Rating
    7.8
    Unranked
    In Log Management
    Comparisons
    Learn More
    Overview

    DNIF HYPERCLOUD is a cloud native platform that brings the functionality of SIEM, UEBA and SOAR into a single continuous workflow to solve cybersecurity challenges at scale. DNIF HYPERCLOUD is the flagship SaaS platform from NETMONASTERY that delivers key detection functionality using big data analytics and machine learning. NETMONASTERY aims to deliver a platform that helps customers in ingesting machine data and automatically identify anomalies in these data streams using machine learning and outlier detection algorithms. The objective is to make it easy for untrained engineers and analysts to use the platform and extract benefit reliably and efficiently.

    Beats is the platform for single-purpose data shippers. They install as lightweight agents and send data from hundreds or thousands of machines to Logstash or Elasticsearch.

    Sample Customers
    Mahindra & Mahindra, Tata Consultancy Services (TCS), ICICI Bank, Yes Bank, Tata Motors, RBL Bank
    Sprint
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company18%
    Financial Services Firm16%
    Real Estate/Law Firm11%
    Construction Company10%
    VISITORS READING REVIEWS
    Financial Services Firm26%
    Computer Software Company14%
    Real Estate/Law Firm14%
    Construction Company9%
    Company Size
    VISITORS READING REVIEWS
    Small Business29%
    Midsize Enterprise15%
    Large Enterprise55%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise9%
    Large Enterprise70%
    Buyer's Guide
    Log Management
    April 2024
    Find out what your peers are saying about Splunk, Datadog, Wazuh and others in Log Management. Updated: April 2024.
    767,667 professionals have used our research since 2012.

    DNIF HYPERCLOUD is ranked 24th in Log Management with 7 reviews while Elastic Beats doesn't meet the minimum requirements to be ranked in Log Management. DNIF HYPERCLOUD is rated 7.6, while Elastic Beats is rated 8.0. The top reviewer of DNIF HYPERCLOUD writes "Development from open sources is very valuable but a huge infrastructure is required". On the other hand, the top reviewer of Elastic Beats writes "A robust solution with a whole spectrum of features that's extremely scalable". DNIF HYPERCLOUD is most compared with IBM Security QRadar, Splunk Enterprise Security, Microsoft Sentinel and Wazuh, whereas Elastic Beats is most compared with .

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    We monitor all Log Management 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.