DNIF HYPERCLOUD vs Splunk User Behavior Analytics comparison

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267 views|160 comparisons
85% willing to recommend
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2,321 views|1,443 comparisons
100% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between DNIF HYPERCLOUD and Splunk User Behavior Analytics based on real PeerSpot user reviews.

Find out in this report how the two User Entity Behavior Analytics (UEBA) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed DNIF HYPERCLOUD vs. Splunk User Behavior Analytics Report (Updated: March 2024).
767,995 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
"Great for scaling productivity for log monitoring purposes.""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 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 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.""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 response time on queries is super-fast."

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"The product is at the forefront of auto-remediation networking. It's great.""It is a solution that helps test and measure customer satisfaction.""Splunk is more user-friendly than some competing solutions we tried.""The solution is definitely scalable.""The solution appears to be stable, although we haven't used it heavily.""Because of some of the visualizations that we utilize, we are able to understand strange, unusual traffic on our networks.""This is a good security product.""The solution is fast, flexible, and easy to use."

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Cons
"Dependency on the DNIF support team was frustrating.""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.""There are currently some issues with machine learning plug-ins.""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 EBA could be improved.""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."

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"The initial setup was complex because some of the configurations that we required needed customization.""It could be easier to scale the solution if you are using it on-premise, not in the cloud.""Currently, a lot of network operations need improvement. We still need people to handle incidents. Our vision is to leverage status and convert it directly from the network devices. It would be ideal if we could take action using APIs and API code and remove manual processes.""They should work to add more built-in correlation searches and more use cases based on worldwide customer experiences. They need more ready-made use cases.""There are occasional bugs.""I would like improved downward integration with other tools such as McAfee and other GCP solutions.""If the price was lowered and the setup process was less complex, I would consider rating it higher.""The correlation engine should have persistent and definable rules."

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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 →

  • "I hope we can increase the free license to be more than 5 gig a day. This would help people who want to introduce a POC or a demo license for the solution."
  • "My biggest complaint is the way they do pricing... You can never know the pricing for next year. Every single time you adjust to something new, the price goes up. It's impossible to truly budget for it. It goes up constantly."
  • "There are additional costs associated with the integrator."
  • "The licensing costs is around 10,000 dollars."
  • "Pricing varies based on the packages you choose and the volume of your usage."
  • "I am not aware of the price, but it is expensive."
  • More Splunk User Behavior Analytics 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 »
    Top Answer:We are really pleased with Splunk and its features. It would be practically impossible to function without it To provide a general overview of the system, it's important to note that the standard… more »
    Top Answer:I am not aware of the price, but it is expensive. A rough estimate would be around 150 gigabytes, given the huge amount of data. At the moment there are no additional costs for maintenance.
    Top Answer:Currently, we do not have any specific improvement projects in progress. However, we have partnered with some companies that are constantly working on improving the system. Therefore, I believe it's… more »
    Ranking
    Views
    267
    Comparisons
    160
    Reviews
    5
    Average Words per Review
    774
    Rating
    7.8
    Views
    2,321
    Comparisons
    1,443
    Reviews
    5
    Average Words per Review
    374
    Rating
    8.6
    Comparisons
    Also Known As
    Caspida, Splunk UBA
    Learn More
    Splunk
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    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.

    Splunk User Behavior Analytics is a behavior-based threat detection is based on machine learning methodologies that require no signatures or human analysis, enabling multi-entity behavior profiling and peer group analytics for users, devices, service accounts and applications. It detects insider threats and external attacks using out-of-the-box purpose-built that helps organizations find known, unknown and hidden threats, but extensible unsupervised machine learning (ML) algorithms, provides context around the threat via ML driven anomaly correlation and visual mapping of stitched anomalies over various phases of the attack lifecycle (Kill-Chain View). It uses a data science driven approach that produces actionable results with risk ratings and supporting evidence that increases SOC efficiency and supports bi-directional integration with Splunk Enterprise for data ingestion and correlation and with Splunk Enterprise Security for incident scoping, workflow management and automated response. The result is automated, accurate threat and anomaly detection.

    Sample Customers
    Mahindra & Mahindra, Tata Consultancy Services (TCS), ICICI Bank, Yes Bank, Tata Motors, RBL Bank
    8 Securities, AAA Western, AdvancedMD, Amaya, Cerner Corporation, CJ O Shopping, CloudShare, Crossroads Foundation, 7-Eleven Indonesia
    Top Industries
    VISITORS READING REVIEWS
    Computer Software Company19%
    Financial Services Firm15%
    Real Estate/Law Firm11%
    Construction Company10%
    REVIEWERS
    Financial Services Firm44%
    Insurance Company11%
    Government11%
    Security Firm11%
    VISITORS READING REVIEWS
    Financial Services Firm14%
    Computer Software Company14%
    Government10%
    Manufacturing Company7%
    Company Size
    VISITORS READING REVIEWS
    Small Business29%
    Midsize Enterprise16%
    Large Enterprise55%
    REVIEWERS
    Small Business31%
    Midsize Enterprise31%
    Large Enterprise38%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise12%
    Large Enterprise69%
    Buyer's Guide
    DNIF HYPERCLOUD vs. Splunk User Behavior Analytics
    March 2024
    Find out what your peers are saying about DNIF HYPERCLOUD vs. Splunk User Behavior Analytics and other solutions. Updated: March 2024.
    767,995 professionals have used our research since 2012.

    DNIF HYPERCLOUD is ranked 9th in User Entity Behavior Analytics (UEBA) with 7 reviews while Splunk User Behavior Analytics is ranked 2nd in User Entity Behavior Analytics (UEBA) with 17 reviews. DNIF HYPERCLOUD is rated 7.6, while Splunk User Behavior Analytics is rated 8.2. 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 Splunk User Behavior Analytics writes "Easy to configure and easy to use solution that integrates with many applications and scripts ". DNIF HYPERCLOUD is most compared with IBM Security QRadar, Splunk Enterprise Security, Microsoft Sentinel and Wazuh, whereas Splunk User Behavior Analytics is most compared with Darktrace, Microsoft Defender for Identity, IBM Security QRadar, Varonis Datalert and Cynet. See our DNIF HYPERCLOUD vs. Splunk User Behavior Analytics report.

    See our list of best User Entity Behavior Analytics (UEBA) vendors.

    We monitor all User Entity Behavior Analytics (UEBA) 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.