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DNIF HYPERCLOUD vs Datadog comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 13, 2025

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
3rd
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
188
Ranking in other categories
Application Performance Monitoring (APM) and Observability (1st), Network Monitoring Software (4th), IT Infrastructure Monitoring (2nd), Container Monitoring (1st), Cloud Monitoring Software (2nd), AIOps (1st), Cloud Security Posture Management (CSPM) (7th)
DNIF HYPERCLOUD
Ranking in Log Management
51st
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
8
Ranking in other categories
Security Information and Event Management (SIEM) (55th), User Entity Behavior Analytics (UEBA) (22nd), Security Orchestration Automation and Response (SOAR) (29th)
 

Mindshare comparison

As of August 2025, in the Log Management category, the mindshare of Datadog is 6.0%, down from 7.1% compared to the previous year. The mindshare of DNIF HYPERCLOUD is 0.2%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Log Management
 

Featured Reviews

reviewer820579 - PeerSpot reviewer
Single pane of glass, easy to share dashboards, and good for monitoring
We've had some issues where we had Datadog automatically turned on in AWS regions that we weren't using, which incurred a small but steady cost that amounted to tens of thousands of dollars spent over a few weeks. I wish there was a global setting that lets an admin restrict which regions DD is turned on in as a default setup step. Sometimes, the APM service dashboard link isn't sharable. I click something in the service catalog, and on that service's APM default view, I try to share a link to that with a teammate, and they reach a blank or error screen. I wish there was more organization and detail in the suggestions when I use the query editor. I'm never quite sure when the autofill dropdown shows up if I'm seeing some custom tag or some default property, so I have to know exactly what I'm looking for in order to build a chart. It's hard to navigate and explore using the query autofill suggestions without knowing exactly what tag to look for. It's been a bit hard to understand how data gets sampled or how many data points a particular dashboard value is using. We've had questions over the RUM metrics that we see and we had to ask for help with how values are calculated, bin sizes, etc to get confidence in our data.
Kishore Tiwari - PeerSpot reviewer
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

"For us to have visibility into our app stack and the hardware we run has been highly beneficial."
"It has enhanced the performance of my team."
"The solution is sufficiently stable."
"It has a high-level insight into the infrastructure model of the application and provides important detailed data on the host and metrics, which is the main concern of our customers."
"The initial setup is very straightforward."
"Datadog's seamless integration with Slack and PagerDuty helped us to receive alerts right to the most common notification methods we use (our mobile devices and Slack)."
"The most valuable aspect is the APM which can monitor the metrics and latencies."
"The many dozens of integrations that the solution brings out of the box are excellent."
"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 response time on queries is super-fast."
"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 dashboard is helpful, and it creates visualizations to let staff review event data and identify patterns and anomalies."
"The beauty of the solution is that you can develop infrastructure for a data lake using open sources that are separate from the licenses."
"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."
 

Cons

"Datadog is so feature-rich that it is often hard to onboard new folks and tough to decide where to invest time."
"Datadog isn't as mature as some of the established players like Dynatrace or Splunk. It's a new product, so they are constantly releasing new features, and I don't have much to complain about."
"Its pricing model can be improved. Its settings should be improved for a better understanding of billing. They should also provide some alerts when there is an increase in the usage. For example, if there is 20% more increase from one week to another, the customer should get an alert."
"We have found that some of the different options for filtering for logs ingestion, APM traces and span ingestion, and RUM sessions vs replay settings can be hard to discover and tough to determine how to adjust and tweak for both optimal performance and monitoring as well as for billing within the console."
"Geo-data is also something very critical that we hope to see in the future."
"Graph filters for logs need to be set manually which works well for JSON but not for unstructured logs."
"Datadog has a lot of features kind of cramped into one dashboard. It's quite hard to get around what feature does exactly what. There was a steep learning curve, trying to navigate through menus."
"The error traceability is an area that can 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 EBA could be improved."
"The solution's command line should be simpler so that routine commands can be used."
"Dependency on the DNIF support team was frustrating."
"I feel that DNIF needs to invest more in marketing, considering that it operates at a very competitive speed."
"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."
"There are currently some issues with machine learning plug-ins."
"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."
 

Pricing and Cost Advice

"Pricing seemed easy until the bill came in and some things were not accounted for."
"This solution is budget friendly."
"The tool is open-source."
"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."
"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."
"The pricing came up a bit compared to their competitors. It is not that the price has risen, but that the competitors have gone down. They keep adding more features that I would have expected to be baked in at a more nominal price. I have been increasingly dissatisfied with the pricing, but not enough to jump ship."
"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."
"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."
"The solution requires a huge infrastructure and that is costly."
"The pricing is based on the log size."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
14%
Manufacturing Company
8%
Healthcare Company
5%
Transportation Company
10%
Media Company
9%
Computer Software Company
8%
Construction Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

Any advice about APM solutions?
There are many factors and we know little about your requirements (size of org, technology stack, management systems, the scope of implementation). Our goal was to consolidate APM and infra monitor...
Datadog vs ELK: which one is good in terms of performance, cost and efficiency?
With Datadog, we have near-live visibility across our entire platform. We have seen APM metrics impacted several times lately using the dashboards we have created with Datadog; they are very good c...
Which would you choose - Datadog or Dynatrace?
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 ...
What needs improvement with DNIF HYPERCLOUD?
A lot of people don't know about DNIF HYPERCLOUD, but they do know about products like Splunk, QRadar, ArcSight, and some other SIEM solutions. DNIF is not a known name in the market. From an impro...
What is your primary use case for DNIF HYPERCLOUD?
DNIF HYPERCLOUD is a good SIEM solution. One of the tools' features is very high scalability in terms of the events generated per second. The product is aligned with the MITRE ATT&CK framework....
What advice do you have for others considering DNIF HYPERCLOUD?
The tool's ability in the area of its analytic capabilities has enhanced our company's security poster in a good way, especially when compared to some of the other competitors in the market, like S...
 

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: July 2025.
865,384 professionals have used our research since 2012.