


IBM Security QRadar and NetWitness NDR compete in the security information and event management space. QRadar holds an advantage in ease of integration and deployment, while NetWitness NDR is preferred for its incident response capabilities and cost-effectiveness.
Features: IBM Security QRadar is known for its ease of integration, deployment, and comprehensive pre-canned rules beneficial for real-time alerting and user-behavior analytics. It provides advanced data enrichment and visualization options. NetWitness NDR offers robust incident response capabilities, seamless integration with third-party applications, and impressive network capture and traffic detailing, offering granular threat visibility.
Room for Improvement: QRadar could enhance customization flexibility, SOAR system integration, and simplify its complex reporting mechanisms. Users also note the need for better playbooks and reduced false positives. NetWitness NDR might improve its integration with non-native applications, dashboard enhancements, and more efficient scalability. Enhancements in threat intelligence integration and automation could boost its effectiveness.
Ease of Deployment and Customer Service: QRadar supports a wide range of deployment options, including hybrid and public cloud models, with comprehensive documentation. However, IBM’s technical support receives mixed reviews. NetWitness NDR primarily offers on-premises deployment and consistent technical support, but responsiveness during critical issues could improve.
Pricing and ROI: QRadar is viewed as expensive, particularly for smaller businesses, though its features often justify the cost. Flexible licensing models help budget adjustments, but additional support and integration costs may escalate. NetWitness NDR is seen as a cost-effective alternative, providing notable ROI despite offering fewer features. The pricing reflects integration needs and extra service charges.
Since we started working with Torq, I am handling much fewer alerts. It is becoming really easy for me to handle an alert.
We have seen a return on investment, targeting a $600,000 ROI for the year.
I have seen a return on investment with Torq, as the automation reduces the number of employees needed and significantly saves both time and resources.
With SOAR, the workflow takes one minute or less to complete the analysis.
AWS gives the chance to implement a solution out of the box with use cases that are already in IBM Security QRadar.
Investing this amount was very much worth it for my organization.
My impression of their technical support during the initial setup was that they were helpful, responded within a reasonable timeframe, and provided exactly what we needed.
The speed and quality of their answers have been pretty good, as I usually get a response within 24 hours, and they follow up well.
We can always get an answer, and the support team are experts in their own system.
They assist with advanced issues, such as hardware or other problems, that are not part of standard operations.
Support needs to understand the issue first, then escalate it to the engineering team.
The support is really good; for instance, if a critical ticket is submitted, you will get paged right away as it gets logged, and their analyst will look into it, letting you know as soon as possible so you can work on it.
Its scalability is good because it has a cloud-native architecture and it expands dynamically to handle thousands of alerts at the same time.
Torq's scalability is a notable strength, as its workflow-based automation allows expansion from managing a few repetitive security tasks to handling more complex and high-volume SOC operations.
Our case management is super scalable.
For EPS license, if you increase or exceed the EPS license, you cannot receive events.
We have been using Torq for one and a half years, but we have experienced no downtime.
I evaluate it based on service availability, workflow execution reliability, integration failures, and incident history.
Most of the time, the system is stable as long as the components that they integrate with are stable.
On cloud, you don't see any disconnections or instability.
I think QRadar is stable and currently satisfies my needs.
The product has been stable so far.
Torq should offer default templates that can directly scan firewall data and automate actions.
The AI value depends on maturity. Real value depends heavily on telemetry, integration depth, and workflow design, all of which rely on how mature customers are in their SOC department.
It was able to capture data but was unable to differentiate between the agent hostname we are using and the hostname that resides on the back end of the Internet.
We receive logs from different types of devices and need a way to correlate them effectively.
If AI-related support can suggest rules and integrate with existing security devices like MD, IPS, this SIM can create more relevant rules.
IBM Security QRadar does not support Canvas, so we had to create custom scripts and workarounds to pull logs from Canvas.
When they bring more and more value into the platform, it makes more sense to pay that price, but still, it is expensive.
Before deciding to implement Torq, I considered that compared to our old case management platform, Torq was a much better price and had a lot better value for what you get out of the platform, which was a key consideration for the company.
It is an expensive solution, not an inexpensive solution, but we get through the flexibility.
Splunk is more expensive than IBM Security QRadar.
It was costly mainly because of the value you can get right now compared to other solutions.
It depends on how much you want to spend.
Torq's unified platform approach to AI SOC automation and case management has significantly benefited us by integrating the case management platform with the automation, which saves time compared to managing multiple point solutions across our security stack.
The fact that I can build whatever I want within my own imagination and skills without relying on code is the best thing about Torq.
You can copy and paste a cURL command. If you have documentation or APIs, you usually have an example on the side. You basically have all the information on how the API call should be. You can just copy that and paste it into a step, and it will just build the step for you.
Recently, I faced an incident, a cyber incident, and it was detected in real time.
IBM Security QRadar gives the opportunity to improve the time to market of the releases with a great evaluation of cybersecurity breaches.
Compared to ArcSight, Splunk, or any other SIEM tools where you need their processing language such as structured query language, SPL, and in Sentinel there is KQL query languages, IBM Security QRadar doesn't require reliance on query languages.

| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 7 |
| Large Enterprise | 13 |
| Company Size | Count |
|---|---|
| Small Business | 93 |
| Midsize Enterprise | 39 |
| Large Enterprise | 107 |
| Company Size | Count |
|---|---|
| Small Business | 10 |
| Midsize Enterprise | 2 |
| Large Enterprise | 6 |
Torq is the enterprise AI SOC solution that effectively combines adaptive insights and automation to handle critical threats efficiently. It manages threat lifecycles, swiftly moving from triage to response, ensuring effective risk management.
Torq is designed to streamline security operations by aggregating telemetry across your security stack. It investigates significant risks and manages threats from triage to containment and remediation. This AI-driven tool enhances the capabilities of your SecOps team, allowing them to achieve more impactful results without introducing complicated processes.
What are the key features of Torq?
Why consider Torq based on reviews?
In industries like finance and healthcare, Torq shows effectiveness by adapting to specific risk scenarios often encountered in these fields. Its integration with existing infrastructures makes it a valuable asset for maintaining stringent security standards, essential for protecting critical data and operations in diverse high-stakes environments.
IBM Security QRadar offers real-time threat detection, data correlation, and integration with third-party solutions, providing a user-friendly interface, scalability, and extensive reporting capabilities for SIEM needs.
IBM Security QRadar is designed for comprehensive security monitoring in diverse environments, aiding sectors like telecom and finance with advanced threat detection and breach management. It aggregates data and analyzes user behavior, while its customizable and out-of-the-box rules deliver robust security insights and vulnerability management. The platform seeks enhancements in integration, performance, and user interface, with a focus on AI and cloud service compatibility.
What are the most important features of IBM Security QRadar?Telecom, finance, and cloud-based industries implement IBM Security QRadar for threat detection, compliance, and security monitoring. It is deployed for log collection and correlation, user behavior analytics, and ensuring secure data transfer and incident management, focusing on compliance and anomaly detection.
NetWitness NDR provides robust network security features, offering full visibility and effective incident response. Its seamless integration and user-friendly interface support malware detection and real-time threat tracking.
NetWitness NDR stands out for its comprehensive traffic details and compatibility across operating systems. It features a unified dashboard and lightweight installation, making it user-friendly without IT support. The system supports orchestration features and user behavior analytics. While deployment is somewhat modular and complex, it serves well for network security, malware analysis, and digital forensics. NetWitness integrates smoothly with third-party apps using its intuitive API, though improvements could be made in areas like SOAR integration, hunting features, and scalability, alongside addressing pricing and licensing complexities.
What are NetWitness NDR's Key Features?Banks and telecom companies utilize NetWitness NDR for detecting indicators of compromise, analyzing intrusion history, and providing risk scores. It functions as both a SIEM tool and a network forensic instrument, proving essential for sectors focused on network security and threat prevention.
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