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DNIF HYPERCLOUD vs Gigamon Deep Observability Pipeline comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Sep 18, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

DNIF HYPERCLOUD
Ranking in Security Information and Event Management (SIEM)
46th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
8
Ranking in other categories
Log Management (46th), User Entity Behavior Analytics (UEBA) (19th), Security Orchestration Automation and Response (SOAR) (28th)
Gigamon Deep Observability ...
Ranking in Security Information and Event Management (SIEM)
43rd
Average Rating
8.6
Reviews Sentiment
6.5
Number of Reviews
9
Ranking in other categories
Application Performance Monitoring (APM) and Observability (41st), Event Monitoring (15th), Data Loss Prevention (DLP) (34th), Web Application Firewall (WAF) (34th), Advanced Threat Protection (ATP) (25th), Network Packet Broker (NPB) (1st), Network Detection and Response (NDR) (16th)
 

Mindshare comparison

As of July 2026, in the Security Information and Event Management (SIEM) category, the mindshare of DNIF HYPERCLOUD is 1.1%, up from 0.5% compared to the previous year. The mindshare of Gigamon Deep Observability Pipeline is 0.5%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Security Information and Event Management (SIEM) Mindshare Distribution
ProductMindshare (%)
Gigamon Deep Observability Pipeline0.5%
DNIF HYPERCLOUD1.1%
Other98.4%
Security Information and Event Management (SIEM)
 

Featured Reviews

Kishore Tiwari - PeerSpot reviewer
Deputy General Manager - Information Security (Lead ISA) at a energy/utilities company with 1,001-5,000 employees
Development from open sources is very valuable but a huge infrastructure is required
The solution's command line should be simpler so that routine commands can be used. The search configuration is a bit different than other OEMs or SIEM solutions like ArcSight or QRadar that are easy to search because they operate similarly. The logic is there and the solution supplies a pretty good explanation. Basically, DNIF spelled out is the opposite of FIND. You have to find commands whenever you want to search something. For example, a highway gets you to your destination but there is an alternate way people don't yet know about. Gartner or Forrester haven't yet studied it. We were a bit nervous when we were trying to get familiar with the solution. We wondered if we could realize ROI because the commands and ways of pulling data were different to us. We raised a case with the support team and their professionals provided the needed support. The command line is user friendly once you understand it. If you need immediate use, then you might want to get assistance from someone who is well-versed in methods for using key patterns to find things. Lengthier files for threat hunting or analysis are needed. The correlation happens, but exporting a large number of files to abstract them is not possible. For example, I want to present raw data to management so I should be able to customize a date range in my query and download the files.
TN
Senior Relationship Banker at Joint stock Commercial Bank for Foreign Trade of V
Experience boosts operational efficiency while performance sees room for improvement
I don't have specific information on whether it was purchased on the AWS marketplace or somewhere else. I am working with Dynatrace Operator. I am also working with Algosec, Alluvio, CrowdStrike, Firemon, Gigamon Deep Observability Pipeline, and other solutions. I think it's a good tool, and I am satisfied with it. We have not stored cloud workloads with Gigamon Deep Observability Pipeline yet; we are still on-premises. The technical support takes about one to two hours to respond, which is acceptable. I am satisfied with the scalability of the product. The interface is good.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The solution is quite stable and offers good performance, it also works on a virtual machine and we haven't found any issues with it so far, it's been reliable."
"If you're an enterprise company and want to scale your productivity for log monitoring purposes, I found DNIF a better option than Splunk which has more complex software."
"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 most valuable feature of the solution is the number of EPS it can handle."
"Has a great search capability."
"The response time on queries is super-fast."
"The benefit of DNIF was that the solution was able to detect any anomalies and identify and prevent any possible security threats or attacks."
"DNIF is much faster, much more responsive, and far superior when compared to competitive tools."
"The Pipeline's Comprehensive Insights into data flows have helped improve operational efficiency and security."
"We use Gigamon for network visibility."
"It has high stability."
"It offers straightforward integration."
"The most valuable feature is NetFlow."
"The most valuable feature for improving network visibility with Gigamon is the packet filtering capability."
"The tool's most valuable feature is the encryption feature. From a security perspective, the solution hasn't significantly strengthened our security posture. However, it has greatly improved performance by streamlining encryption processes and avoiding encryption at multiple layers. This has also simplified troubleshooting, as we can whitelist certain processes."
"The solution is straightforward to set up."
 

Cons

"The EBA could be improved."
"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."
"The solution's command line should be simpler so that routine commands can be used."
"DNIF HYPERCLOUD is not a stable product compared to other tools like IBM QRadar."
"We have some issues with machine learning plug-ins and I believe they're working on a solution for that."
"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."
"The solution should be able to connect to endpoints, such as desktops and laptops."
"In terms of improvement, while the initial setup is not overly complicated, we did encounter a few issues."
"The challenge is monitoring the cloud network."
"The security should be improved."
"They should increase the solution's cluster capacity."
"It only inspects a specific kind of traffic. There should be different kinds of use cases."
"The graphical user interface could be improved."
"Gigamon Deep Observability Pipeline needs to improve its performance. I face issues with performance because we use SPAN, and the SPAN traffic is not good."
"Its filtering feature needs improvement."
 

Pricing and Cost Advice

"Price-wise, the product is quite economical. I rate the solution's price as three or four on a scale of one to ten, where one is considered to be a very economically priced tool."
"The solution requires a huge infrastructure and that is costly."
"The pricing is based on the log size."
"The solution is highly-priced."
"I would rate the solution as expensive, around an eight or nine out of ten. There are other competitive solutions available."
"The solution's price is reasonable."
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Top Industries

By visitors reading reviews
Construction Company
16%
Comms Service Provider
8%
Outsourcing Company
8%
Financial Services Firm
7%
Financial Services Firm
14%
Computer Software Company
9%
Manufacturing Company
9%
Healthcare Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise3
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise5
 

Questions from the Community

Ask a question
Earn 20 points
What needs improvement with Gigamon Deep Observability Pipeline?
Gigamon Deep Observability Pipeline needs to improve its performance. I face issues with performance because we use SPAN, and the SPAN traffic is not good. They need to improve their performance.
What is your primary use case for Gigamon Deep Observability Pipeline?
I am working with Gigamon Deep Observability Pipeline and Firemon, and I have been working with it for a year.
What advice do you have for others considering Gigamon Deep Observability Pipeline?
I don't have specific information on whether it was purchased on the AWS marketplace or somewhere else. I am working with Dynatrace Operator. I am also working with Algosec, Alluvio, CrowdStrike, F...
 

Also Known As

No data available
Gigamon, GigaSecure
 

Overview

 

Sample Customers

Mahindra & Mahindra, Tata Consultancy Services (TCS), ICICI Bank, Yes Bank, Tata Motors, RBL Bank
Amica Insurance, College of William & Mary, Gamma, IntercontinentalExchange, OppenheimerFunds
Find out what your peers are saying about DNIF HYPERCLOUD vs. Gigamon Deep Observability Pipeline and other solutions. Updated: June 2026.
902,894 professionals have used our research since 2012.