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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) (6th), AI Observability (1st)
DNIF HYPERCLOUD
Ranking in Log Management
45th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
8
Ranking in other categories
Security Information and Event Management (SIEM) (45th), User Entity Behavior Analytics (UEBA) (19th), Security Orchestration Automation and Response (SOAR) (28th)
 

Mindshare comparison

As of August 2026, in the Log Management category, the mindshare of Datadog is 3.9%, down from 6.0% compared to the previous year. The mindshare of DNIF HYPERCLOUD is 1.2%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Log Management Mindshare Distribution
ProductMindshare (%)
Datadog3.9%
DNIF HYPERCLOUD1.2%
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

"Thanks to frequent concurrent deployments, the DataDog alerts monitors allow us quickly detect issues if anything occurs."
"It is exceptionally helpful for making our engineering more data-driven."
"We have found that we're able to get in and out of troubleshooting issues much more rapidly, which in turn, of course, enables us to spend more time on our products."
"Real user monitoring has made triaging any possible bugs our users might face a lot easier."
"It has provided visibility with ease of implementation and allowed multiple teams to quickly onboard it."
"Datadog was a way simpler solution to setting up browser and API tests quickly."
"Datadog has a very good visualization for my complete infrastructure and network traffic, which enabled me to create a capacity plan."
"By moving to Datadog, we did not need to manage our own monitoring infrastructure anymore."
"The response time on queries is super-fast."
"It was one of the first SIEM tools I saw that had that particular MITRE table."
"The beauty of the solution is that you can develop infrastructure for a data lake using open sources that are separate from the licenses."
"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."
"DNIF is much faster, much more responsive, and far superior when compared to competitive tools."
"Has a great search capability."
"The most valuable feature of the solution is the number of EPS it can handle."
"Great for scaling productivity for log monitoring purposes."
 

Cons

"The product can be improved by allowing the grouping of APIs to add variables. That way, any API with a unique ID could be grouped together."
"The wide range of products Datadog now offers can be a bit intimidating to developers."
"It is hard to educate an entire team. There is a big learning curve."
"The ability to find what you are looking for when starting out could be improved."
"Network device and performance monitoring could be improved, as we've faced some limitations in this area."
"There are things about it that we would like to be fixed, such as it is taking averages of average. This results in data that we don't expect, but overall we are happy with it."
"Datadog can be improved because sometimes it seems it has not been developed for enterprises."
"I'd rate Datadog support four out of 10. It was primarily an issue with support in the Asia-Pacific region."
"Dependency on the DNIF support team was frustrating."
"The EBA could be improved."
"I used version 8 which was not at all stable. The services and processor keep going down, we had to manually keep them up increasing storage space because services are down, and logs not processed."
"The solution's command line should be simpler so that routine commands can be used."
"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."
"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."
"DNIF HYPERCLOUD is not a stable product compared to other tools like IBM QRadar."
 

Pricing and Cost Advice

"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."
"It has always scaled for us. Cost scales up too, but that is not necessarily a bad thing. It's reasonable for what they're providing."
"It didn't scale well from the cost perspective. We had a custom package deal."
"The cost is high and this can be justified if the scale of the environment is big."
"The solution's pricing depends on project volume."
"The pricing and licensing through AWS Marketplace has been good. It would be nice if it was cheaper, but their pricing is reasonable for what it is. Sometimes, for their newer features, they charge as if it's fully fleshed out, even though it is a newer feature and it may have less stuff than their other items."
"It has a module-based pricing model."
"Pricing seemed easy until the bill came in and some things were not accounted for."
"The solution requires a huge infrastructure and that is costly."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Manufacturing Company
9%
Computer Software Company
8%
Outsourcing Company
6%
Construction Company
16%
Outsourcing Company
10%
Comms Service Provider
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
 

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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: August 2026.
909,725 professionals have used our research since 2012.