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DNIF HYPERCLOUD vs Datadog comparison

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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 (2nd), IT Infrastructure Monitoring (1st), Container Monitoring (3rd), Cloud Monitoring Software (1st), AIOps (1st), Cloud Security Posture Management (CSPM) (6th), AI Observability (1st)
DNIF HYPERCLOUD
Ranking in Log Management
42nd
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) (27th)
 

Mindshare comparison

As of October 2026, in the Log Management category, the mindshare of Datadog is 3.7%, down from 5.7% compared to the previous year. The mindshare of DNIF HYPERCLOUD is 1.1%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Log Management Mindshare Distribution
ProductMindshare (%)
Datadog3.7%
DNIF HYPERCLOUD1.1%
Other95.2%
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

"Straightforward to integrate and automate."
"Datadog has positively impacted our organization because our customers are very happy using it."
"Datadog's learning platform is second to none."
"Datadog has helped my organization improve a lot of response time because we get alerts the minute it happens, which is our only means to reduce incident response time."
"Our usage of Datadog has allowed us to improve our observability at great lengths."
"The full stack of integrations made it easier to monitor the different technologies and platform providers, including Software as a Service providers, that otherwise would need a lot of work and customization to be able to see what is happening."
"The flexibility to create notebooks and dashboards and fully customize them gives us a lot of power to track the exact services and endpoints we are working on."
"The most valuable aspect for us is to have everything in the same place."
"Great for scaling productivity for log monitoring purposes."
"The dashboard is helpful, and it creates visualizations to let staff review event data and identify patterns and anomalies."
"The most valuable feature of the solution is the number of EPS it can handle."
"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."
"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."
"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."
"It was one of the first SIEM tools I saw that had that particular MITRE table."
 

Cons

"Particularly as Datadog starts offering more platform capabilities like APM, Watchdog, shift left initiatives like instrumentation, continuous testing, intelligent test runner, and Synthetic and real user monitoring, the UI can become more and more clunky, giving users a very frustrating experience."
"At the beginning, when we started throwing logs at it, there was a bit of hiccup. However, this was during their beta period, so hiccups were expected."
"We need to learn more about the session reply feature inside of DD."
"The solution should provide alerts for cloud outages."
"The cost is high and this can be justified if the scale of the environment is big. Datadog needs to provide better pricing for large customers."
"We would like to see smaller or shorter tutorials and video sessions."
"It would be ideal if the product offered a bit more monitoring from our dashboard."
"There are some areas on log filtering screens where the user interface can take some getting used to."
"I feel that DNIF needs to invest more in marketing, considering that it operates at a very competitive speed."
"The solution should be able to connect to endpoints, such as desktops and laptops."
"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."
"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 EBA could be improved."
"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."
"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."
 

Pricing and Cost Advice

"Datadog does not provide any free plans to use the solution. When I start with a proof of concept it would be sensible to have a free plan to test the tool and check whether it fits the requirements of the project. Before the production stage, it is always good to have a free plan with some limited features, number of requests, or logs."
"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 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."
"This solution is budget friendly."
"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 price of Datadog is reasonable. Other solutions are more expensive, such as AppDynamics."
"Licensing is based on the retention period of logs and metrics."
"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%
Manufacturing Company
10%
Outsourcing Company
8%
Computer Software Company
7%
Construction Company
15%
Outsourcing Company
14%
Comms Service Provider
11%
Financial Services Firm
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business81
Midsize Enterprise50
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: September 2026.
915,341 professionals have used our research since 2012.