DNIF HYPERCLOUD vs Elastic Observability comparison

NETMONASTERY and Elastic are both solutions in the Log Management category. NETMONASTERY is ranked #52, while Elastic is ranked #14 with an average rating of 8.7. NETMONASTERY holds a 0.6% mindshare in Log Management, compared to Elastic’s 1.2% mindshare. Additionally, 85% of NETMONASTERY users are willing to recommend the solution, compared to 88% of Elastic users who would recommend it.

DNIF HYPERCLOUD

Read 8 DNIF HYPERCLOUD reviews

1,544 Views
772 Comparison Views

85% willing to recommend

Elastic Observability

Read 29 Elastic Observability reviews

8,436 Views
2,025 Comparison Views

88% willing to recommend

DNIF HYPERCLOUD

Elastic Observability

Comparison Buyer's Guide

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Executive SummaryUpdated on Oct 9, 2024

DNIF HYPERCLOUD and Elastic Observability compete in the monitoring and analysis of logs, traces, and metrics. Elastic Observability seems to have the upper hand with its comprehensive features, which users believe justify its higher pricing.

Features: DNIF HYPERCLOUD is noted for its scalability, offering advanced automation capabilities and seamless cloud integration suited for large-scale data processing. Elastic Observability provides robust analytical tools, flexible customization options, and detailed monitoring and diagnostics capabilities that users find advantageous.

Room for Improvement: Users suggest DNIF HYPERCLOUD could enhance its documentation and reporting capabilities and simplify navigation in complex scenarios. Elastic Observability users desire improved integration with third-party tools, a simpler configuration process, and enhancements to streamline user interaction.

Ease of Deployment and Customer Service: DNIF HYPERCLOUD has an efficient deployment process with straightforward setup and responsive customer service. Elastic Observability has a more complex deployment, yet it is supported by strong customer service that effectively addresses issues.

Pricing and ROI: DNIF HYPERCLOUD is seen as a cost-effective solution with low setup costs and a solid return on investment, appealing to budget-conscious buyers. Elastic Observability, despite its higher costs, offers an enhanced ROI through its extensive feature set, which users find to be a worthwhile investment in the long term.

To learn more, read our detailed DNIF HYPERCLOUD vs. Elastic Observability Report (Updated: December 2025).

Buyer's Guide

DNIF HYPERCLOUD vs. Elastic Observability

December 2025

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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 Log Management

52nd

Average Rating

7.6

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Security Information and Event Management (SIEM) (52nd), User Entity Behavior Analytics (UEBA) (22nd), Security Orchestration Automation and Response (SOAR) (28th)

Elastic Observability

Ranking in Log Management

14th

Average Rating

8.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Application Performance Monitoring (APM) and Observability (6th), IT Infrastructure Monitoring (9th), Container Monitoring (4th), Cloud Monitoring Software (7th)

Mindshare comparison

As of January 2026, in the Log Management category, the mindshare of DNIF HYPERCLOUD is 0.6%, up from 0.2% compared to the previous year. The mindshare of Elastic Observability is 1.2%, down from 1.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Log Management Market Share Distribution
Product	Market Share (%)
Elastic Observability	1.2%
DNIF HYPERCLOUD	0.6%
Other	98.2%

Log Management

Featured Reviews

Kishore Tiwari

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.

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Mohammed-Abdelalim

Assistant Vice President at QualityKiosk Technologies Pvt. Ltd.

Has provided powerful customization for unique monitoring needs but needs more out-of-the-box capabilities

In my opinion, the best features of Elastic Observability are their flexibility to integrate with other existing systems and the ability to build a unified monitoring tool that can integrate with existing ones and end-to-end user journeys which require a lot of customizations. The greatest feature in Elastic is the ability to customize. This is similar to my comments about customizable dashboards in Elastic because it's visible to the analyst. However, it's very great. Customizing these dashboards can meet the customer's specific use cases and specific stories that they have in their environment, their special environment that doesn't look like other environments. The dashboarding in Elastic is highly customizable to the level of logos. If the customer wants his company logo in the dashboard, it can be done.

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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. We haven't found any issues with it so far. It's been reliable."

"The response time on queries is super-fast."

"Has a great search capability."

"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 beauty of the solution is that you can develop infrastructure for a data lake using open sources that are separate from the licenses."

"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."

More DNIF HYPERCLOUD pros

"Machine learning is the most valuable feature of this solution."

"The most valued feature of Elastic is its log analytics capabilities."

"It is scalable and supports multitenancy, which is beneficial for MSPs."

"Elastic provides built-in features for queries and report generation. It's a very good tool for monitoring integration capabilities."

"I have built a mini business intelligence system based on Elastic Observability."

"It has always been a stable solution."

"All the features that we use, such as monitoring, dashboarding, reporting, the possibility of alerting, and the way we index the data, are important."

"The Elastic User Interface framework lets us do custom development when needed. You need to have some Javascript knowledge. We need that knowledge to develop new custom tests."

More Elastic Observability pros

Cons

"The solution's command line should be simpler so that routine commands can be used."

"Dependency on the DNIF support team was frustrating."

"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 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... 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."

"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."

"The EBA could be improved."

"It lacked some capabilities when handling on-prem devices, like network observability, package flow analysis, and device performance data on the infrastructure side."

"Elastic Observability needs to have better standardization, logging, and schema."

"Elastic Observability is an excellent product for monitoring and visibility, but it lacks predictive analytics. Most solutions are aligned with the AIOps requirements, but this piece is missing in Elastic and should be included."

"The auto-discovery isn't nearly as good. That's a big portion of it. When you drop the agent onto the JVM and you're trying to figure things out, having to go through and manually do all that is cumbersome."

"I am familiar with Azure Monitor, which I find more user-friendly compared to Elastic, which is a very technical tool."

"They need more skills in the market. There are not enough skills in the market. It is not pervasive enough on the market, in my opinion. In other words, there isn't a big enough user base."

"Elastic Observability could improve asset discovery as the current requirement to push the agent is not ideal."

"The solution needs to use more AI. Once the product onboards AI, users would more effectively be able to track endpoints for specific messages."

More Elastic Observability cons

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."

"So far, there are just the standard licensing fees. Several of the components are embedded in the license or are even open source. They're even free depending on what you use, which makes it even more appealing to someone that is discussing pricing of the solution."

"We will buy a premium license after POC."

"The product’s pricing needs improvement."

"There are two types: cloud and SaaS. They charge based on data ingestion, ingest rate, hard retention, and warm retention. I believe it costs around $25,000 annually to ingest 30GB of data daily. That is the SaaS version. There is also a self-managed license where the customer manages their own infrastructure on-prem. In such cases, there are three license tiers that respectively cost $5,000 annually per node, $7,000 per node, and $12,500 per node."

"Since we are a huge company, Elastic Observability is an affordable solution for us."

"The product is not that cheap."

"The price of Elastic Observability is expensive."

"One needs to pay for the licenses, and it is an annual subscription model right now."

More Elastic Observability pricing and cost advice

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Top Industries

By visitors reading reviews

Transportation Company

10%

Manufacturing Company

Financial Services Firm

Outsourcing Company

Financial Services Firm

16%

Computer Software Company

14%

Manufacturing Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	1
Large Enterprise	3

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	4
Large Enterprise	16

Questions from the Community

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...

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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....

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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...

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What do you like most about Elastic Observability?

Elastic Observability significantly improves incident response time by providing quick access to logs and data across various sources. For instance, searching for specific keywords in logs spanning...

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What is your experience regarding pricing and costs for Elastic Observability?

The problem is their licensing model, which is a bit confusing. Many customers struggle to understand their total cost of ownership because Elastic licensing is not dependent on easy, quantifiable ...

See all answers

What needs improvement with Elastic Observability?

After careful consideration about areas for improvement in Elastic Observability, aspects such as pricing, customization, implementation, and scalability could be improved. As a user of the system,...

See all answers

Comparisons

Splunk Enterprise Security vs DNIF HYPERCLOUD

Compared 16% of the time

Elastic Security vs DNIF HYPERCLOUD

Compared 10% of the time

Seceon Open Threat Management Platform vs DNIF HYPERCLOUD

Compared 8% of the time

IBM Security QRadar vs DNIF HYPERCLOUD

Compared 8% of the time

Fortinet FortiSIEM vs DNIF HYPERCLOUD

Compared 6% of the time

More DNIF HYPERCLOUD Competitors

Sentry vs Elastic Observability

Compared 8% of the time

Dynatrace vs Elastic Observability

Compared 7% of the time

New Relic vs Elastic Observability

Compared 7% of the time

Grafana vs Elastic Observability

Compared 7% of the time

Zabbix vs Elastic Observability

Compared 6% of the time

More Elastic Observability Competitors

Product Reports

Buyer's Guide

DNIF HYPERCLOUD

January 2026

Download DNIF HYPERCLOUD product report

Buyer's Guide

Elastic Observability

January 2026

Download Elastic Observability product report

Overview

DNIF HYPERCLOUD is a cloud native platform that brings the functionality of SIEM, UEBA and SOAR into a single continuous workflow to solve cybersecurity challenges at scale. DNIF HYPERCLOUD is the flagship SaaS platform from NETMONASTERY that delivers key detection functionality using big data analytics and machine learning. NETMONASTERY aims to deliver a platform that helps customers in ingesting machine data and automatically identify anomalies in these data streams using machine learning and outlier detection algorithms. The objective is to make it easy for untrained engineers and analysts to use the platform and extract benefit reliably and efficiently.

NETMONASTERY

Elastic Observability offers a comprehensive suite for log analytics, application performance monitoring, and machine learning. It integrates seamlessly with platforms like Teams and Slack, enhancing data visualization and scalability for real-time insights.

Elastic Observability is designed to support production environments with features like logging, data collection, and infrastructure tracking. Centralized logging and powerful search functionalities make incident response and performance tracking efficient. Elastic APM and Kibana facilitate detailed data visualization, promoting rapid troubleshooting and effective system performance analysis. Integrated services and extensive connectivity options enhance its role in business and technical decision-making by providing actionable data insights.

What are the most important features of Elastic Observability?

Centralized Logging: Streamlines the collection, analysis, and storage of log data.
Powerful Search: Provides robust search capabilities for quick access to relevant information.
Scalability: Supports growing data needs across diverse environments.
Real-time Telemetry: Ensures up-to-date insights and monitoring.
Platform Integration: Seamlessly connects with services like Teams and Slack.
Data Visualization: Enhances visibility with Elastic APM and Kibana.

What benefits and ROI should users explore in reviews?

Cost-effectiveness: Offers significant savings through efficient data management.
Rapid Incident Response: Minimizes downtime with quick troubleshooting tools.
Comprehensive Insights: Supports better business decisions with detailed data analysis.
Performance Tracking: Enables assessment of system effectiveness and improvements.

Elastic Observability is employed across industries for critical operations, such as in finance for transaction monitoring, in healthcare for secure data management, and in technology for optimizing application performance. Its data-driven approach aids efficient event tracing, supporting diverse industry requirements.

Elastic

Sample Customers

Mahindra & Mahindra, Tata Consultancy Services (TCS), ICICI Bank, Yes Bank, Tata Motors, RBL Bank

PSCU, Entel, VITAS, Mimecast, Barrett Steel, Butterfield Bank

Buyer's Guide

DNIF HYPERCLOUD vs. Elastic Observability

December 2025

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