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DNIF HYPERCLOUD vs Datadog comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 25, 2026

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

Datadog
Ranking in Log Management
4th
Average Rating
8.6
Reviews Sentiment
6.9
Number of Reviews
211
Ranking in other categories
Application Performance Monitoring (APM) and Observability (1st), Network Monitoring Software (3rd), IT Infrastructure Monitoring (2nd), Container Monitoring (3rd), Cloud Monitoring Software (1st), AIOps (1st), Cloud Security Posture Management (CSPM) (5th), AI Observability (1st)
DNIF HYPERCLOUD
Ranking in Log Management
46th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
8
Ranking in other categories
Security Information and Event Management (SIEM) (46th), User Entity Behavior Analytics (UEBA) (19th), Security Orchestration Automation and Response (SOAR) (28th)
 

Mindshare comparison

As of July 2026, in the Log Management category, the mindshare of Datadog is 4.0%, down from 6.0% compared to the previous year. The mindshare of DNIF HYPERCLOUD is 1.1%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Log Management Mindshare Distribution
ProductMindshare (%)
Datadog4.0%
DNIF HYPERCLOUD1.1%
Other94.9%
Log Management
 

Featured Reviews

Dhroov Patel - PeerSpot reviewer
Site Reliability Engineer at Grainger
Has improved incident response with better root cause visibility and supports flexible on-call scheduling
Datadog needs to introduce more hard limits to cost. If we see a huge log spike, administrators should have more control over what happens to save costs. If a service starts logging extensively, I want the ability to automatically direct that log into the cheapest log bucket. This should be the case with many offerings. If we're seeing too much APM, we need to be aware of it and able to stop it rather than having administrators reach out to specific teams. Datadog has become significantly slower over the last year. They could improve performance at the risk of slowing down feature work. More resources need to go into Fleet Automation because we face many problems with things such as the Ansible role to install Datadog in non-containerized hosts. We mainly want to see performance improvements, less time spent looking at costs, the ability to trust that costs will stay reasonable, and an easier way to manage our agents. It is such a powerful tool with much potential on the horizon, but cost control, performance, and agent management need improvement. The main issues are with the administrative side rather than the actual application.
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.

Quotes from Members

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

Pros

"Datadog has positively impacted my organization by shortening our time to resolve incidents because it's a central place for getting all the data that we need for troubleshooting."
"Datadog provides a lot of value in terms of adding monitoring and observability to our app."
"Since using Datadog, it has positively impacted our organization by giving us a one-stop shop for multiple applications and services that we can analyze in one spot."
"We enjoy the multistep API tests."
"Its integration definitely stands out. It provides seamless monitoring of all our systems, services, apps, and whatever else we secure and monitor. Visualizations have become simpler with dashboards. We are getting visibility into systems, services, and apps stack through a single pane of glass, which is good. We are able to put logs in context."
"The solution has helped out organization gain improved visibility."
"The solution has improved our organization by expanding the awareness of issues and alerts beyond SRE and really empowering software engineers at a team level to make changes to monitoring and incident responses."
"It provides more cloud data. They tend to just get the way a service would be designed on the cloud."
"The benefit of DNIF was that the solution was able to detect any anomalies and identify and prevent any possible security threats or attacks."
"Great for scaling productivity for log monitoring purposes."
"The most valuable feature of the solution is the number of EPS it can handle."
"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 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."
"DNIF is much faster, much more responsive, and far superior when compared to competitive tools."
"It was one of the first SIEM tools I saw that had that particular MITRE table."
 

Cons

"The sheer amount of products that are included can be overwhelming."
"We would like to see smaller or shorter tutorials and video sessions."
"The product needs a better Datadog agent installation."
"The product is quite complex, and there are so many features that I either didn't know about or wasn't sure how to use."
"In a dynamic environment, it can generate a lot of alert noise if not tuned properly."
"Presently, the billing CSV reports provide insights into billing-related information yet are somewhat limited in functionality, typically offering reports with only three columns."
"More pre-configured "Monitor Alerts" would be helpful."
"The cost does add up quickly, so it can be some effort to justify the necessary outlay to those paying the bills."
"We have some issues with machine learning plug-ins and I believe they're working on a solution for that."
"I feel that DNIF needs to invest more in marketing, considering that it operates at a very competitive speed."
"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... 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."
"DNIF HYPERCLOUD is not a stable product compared to other tools like IBM QRadar."
"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."
"The solution should be able to connect to endpoints, such as desktops and laptops."
 

Pricing and Cost Advice

"It is easy to run up a large bill, so become familiar with the cost of each piece of your bill and use the metrics they supply to estimate and monitor your bill."
"Pricing and licensing are reasonable for what they give you. You get the first five hosts free, which is fun to play around with. Then it's about four dollars a month per host, which is very affordable for what you get out of it. We have a lot of hosts that we put a lot of custom metrics into, and every host gives you an allowance for the number of custom metrics."
"Pricing seemed easy until the bill came in and some things were not accounted for."
"If you do your homework, you'll find that if you're really concerned with cost, it's good."
"I am not satisfied with its licensing. Its payment is based on the exported data, and there was an explosion of the data for three or four weeks. My customer was not alerted, and there was no way for them to see that there has been an explosion of data. They got a big invoice for one or two months. The pricing model of Datadog is based on the data. The customer was quite surprised about not being alerted about this explosion of data. They should provide some kind of alert when there is an increase in usage."
"Sometimes it's very hard to project how much it will cost for the monthly subscription for the next month when you add certain features. Having better visibility of the cost would give a better experience."
"Licensing is based on the retention period of logs and metrics."
"​Pricing seems reasonable. It depends on the size of your organization, the size of your infrastructure, and what portion of your overall business costs go toward infrastructure."
"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 pricing is based on the log size."
"The solution requires a huge infrastructure and that is costly."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Manufacturing Company
9%
Computer Software Company
8%
Outsourcing Company
6%
Construction Company
16%
Comms Service Provider
8%
Outsourcing Company
8%
Financial Services Firm
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business82
Midsize Enterprise49
Large Enterprise100
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise3
 

Questions from the Community

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Our organization ran comparison tests to determine whether the Datadog or Dynatrace network monitoring software was the better fit for us. We decided to go with Dynatrace. Dynatrace offers network ...
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Overview

 

Sample Customers

Adobe, Samsung, facebook, HP Cloud Services, Electronic Arts, salesforce, Stanford University, CiTRIX, Chef, zendesk, Hearst Magazines, Spotify, mercardo libre, Slashdot, Ziff Davis, PBS, MLS, The Motley Fool, Politico, Barneby's
Mahindra & Mahindra, Tata Consultancy Services (TCS), ICICI Bank, Yes Bank, Tata Motors, RBL Bank
Find out what your peers are saying about DNIF HYPERCLOUD vs. Datadog and other solutions. Updated: June 2026.
902,988 professionals have used our research since 2012.