DNIF HYPERCLOUD vs Elastic Observability comparison

NETMONASTERY and Elastic are both solutions in the Log Management category. NETMONASTERY is ranked #49, while Elastic is ranked #14 with an average rating of 8.5. NETMONASTERY holds a 0.3% mindshare in Log Management, compared to Elastic’s 1.3% 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

987 Views
543 Comparison Views

85% willing to recommend

Elastic Observability

Read 28 Elastic Observability reviews

8,986 Views
2,157 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: September 2025).

Buyer's Guide

DNIF HYPERCLOUD vs. Elastic Observability

September 2025

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Helped 869,760 peers since 2012

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

49th

Average Rating

7.6

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Security Information and Event Management (SIEM) (54th), User Entity Behavior Analytics (UEBA) (23rd), Security Orchestration Automation and Response (SOAR) (29th)

Elastic Observability

Ranking in Log Management

14th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Application Performance Monitoring (APM) and Observability (7th), IT Infrastructure Monitoring (10th), Container Monitoring (4th), Cloud Monitoring Software (6th)

Mindshare comparison

As of October 2025, in the Log Management category, the mindshare of DNIF HYPERCLOUD is 0.3%, up from 0.2% compared to the previous year. The mindshare of Elastic Observability is 1.3%, down from 1.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Log Management Market Share Distribution
Product	Market Share (%)
Elastic Observability	1.3%
DNIF HYPERCLOUD	0.3%
Other	98.4%

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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Adelina Craciun

Product Owner at Swisscom

Customization enables tailored monitoring and alerting across departments

The possibility to customize it has been quite useful. Whatever the other departments want to dream up, we implement. Whatever they want to monitor, the granularity of it, the changes in the threshold, and the anomalies that they want reported all require some development. So far, every single request has been fulfilled.

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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 dashboard is helpful, and it creates visualizations to let staff review event data and identify patterns and anomalies."

"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 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 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 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 response time on queries is super-fast."

"The most valuable feature of the solution is the number of EPS it can handle."

More DNIF HYPERCLOUD pros

"It is very stable, and I would rate it ten out of ten based on my interaction with it."

"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."

"The architecture and system's stability are simple."

"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 solution allows us to dig deep into data."

"The product has connectors to many services."

"The price is very less expensive compared to the other solutions."

"I recommend Elastic Observability for its completeness of vision and wide ecosystem."

More Elastic Observability pros

Cons

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

"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 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."

"Dependency on the DNIF support team was frustrating."

"The EBA could be improved."

"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."

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

"When opening tickets, we cannot use our team mailbox."

"Improving code insight related to infrastructure and network, particularly focusing on aspects such as firewalls, switches, routers, and testing would be beneficial."

"Elastic Observability is difficult to use. There are only three options for customization but this can be difficult for our use case. We do not have other options to choose the metrics shown, such as CPU or memory usage."

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

"There is room for improvement regarding its APM capabilities."

"If we had some pre-defined templates for observability that we could start using right away after deploying it – instead of having to build or to change some of the dashboards – that would be helpful."

"The only challenging aspect for new users is often writing the query language."

More Elastic Observability cons

Pricing and Cost Advice

"The pricing is based on the log size."

"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."

"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."

"We have been using the open-source version."

"Elastic Observability's pricing could be better for small-scale users."

"Pricing is one of those situations where the more you use it, the more you pay."

"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."

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

"The price of Elastic Observability is expensive."

"We will buy a premium license after POC."

More Elastic Observability pricing and cost advice

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Top Industries

By visitors reading reviews

Transportation Company

10%

Media Company

Manufacturing Company

University

Financial Services Firm

17%

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	8
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?

Out-of-the-box use cases have room for improvement in Elastic Observability. They don't invest a lot in building out-of-the-box observable use cases, and they are more focusing on giving a very fle...

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Comparisons

Splunk Enterprise Security vs DNIF HYPERCLOUD

Compared 41% of the time

Seceon Open Threat Management Platform vs DNIF HYPERCLOUD

Compared 23% of the time

Fortinet FortiAnalyzer vs DNIF HYPERCLOUD

Compared 14% of the time

IBM Security QRadar vs DNIF HYPERCLOUD

Compared 11% of the time

Fortinet FortiSIEM vs DNIF HYPERCLOUD

Compared 11% of the time

More DNIF HYPERCLOUD Competitors

Sentry vs Elastic Observability

Compared 13% of the time

New Relic vs Elastic Observability

Compared 11% of the time

Dynatrace vs Elastic Observability

Compared 10% of the time

Grafana vs Elastic Observability

Compared 8% of the time

Zabbix vs Elastic Observability

Compared 7% of the time

More Elastic Observability Competitors

Product Reports

Buyer's Guide

DNIF HYPERCLOUD

October 2025

Download DNIF HYPERCLOUD product report

Buyer's Guide

Elastic Observability

October 2025

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

September 2025

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