

IBM Security QRadar and OpenText Behavioral Signals compete in the cybersecurity domain. IBM Security QRadar has the upper hand in scalability and threat detection, while OpenText Behavioral Signals leads in emotional AI analytics.
Features: IBM Security QRadar delivers robust threat intelligence, advanced analytics, and comprehensive security insights. It integrates well with various platforms, allowing seamless data correlation and reducing false positives. OpenText Behavioral Signals offers emotional AI tools for detecting communication behavioral patterns, enhancing its emotional intelligence capabilities, with strong integration features.
Room for Improvement: IBM Security QRadar could enhance its user interface and reduce setup complexity for smaller organizations. Additional improvements in AI-driven anomaly detection are needed for more precision. OpenText Behavioral Signals might build out its threat detection capabilities and better integrate with third-party security tools. Improvement in real-time analytics and expanding its language support could strengthen its offerings.
Ease of Deployment and Customer Service: IBM Security QRadar offers flexible deployment options, both on-premise and cloud, with significant support resources for complex IT environments. OpenText Behavioral Signals focuses on quick cloud-based deployment, with specialized support for AI applications, appealing to businesses looking for rapid integration.
Pricing and ROI: IBM Security QRadar's pricing reflects its diverse features, providing a satisfactory ROI for comprehensive security management. OpenText Behavioral Signals is competitively priced, focusing on AI-driven insights, offering a potentially higher ROI for businesses centered on communication dynamics. The ROI for QRadar benefits organizations needing advanced cybersecurity controls, while Behavioral Signals suits those emphasizing behavioral data analytics.
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.
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.
For EPS license, if you increase or exceed the EPS license, you cannot receive events.
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.
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.
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.
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.
| Product | Mindshare (%) |
|---|---|
| IBM Security QRadar | 5.3% |
| OpenText Behavioral Signals | 0.9% |
| Other | 93.8% |


| Company Size | Count |
|---|---|
| Small Business | 92 |
| Midsize Enterprise | 39 |
| Large Enterprise | 107 |
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.
OpenText Behavioral Signals enhances organizational security monitoring with its robust correlation engine and streamlined dashboard, offering customization to suit different environments like airports or banks.
OpenText Behavioral Signals effectively integrates device logs through its strong correlation engine. The platform's customization options enable tailored alerts to match specific use cases, such as airports or banks. Although it needs more frequent updates to stay aligned with global incidents, it provides a centralized dashboard that ensures comprehensive visibility across networks. Users find the interface intuitive, making rule writing and report access easy, aiding in a comprehensive understanding of the network environment.
What are the key features of OpenText Behavioral Signals?In industries like banking and airports, OpenText Behavioral Signals is implemented for gathering global intelligence from the cloud. It notifies organizations about global attacks and updates its correlation engines. These industries utilize the platform for monitoring and analyzing logs from network devices, security log management, and addressing network challenges like link failures and unauthorized login attempts, ensuring better security posture with behavioral analytics and log integration using Unix and Microsoft-based connectors.
We monitor all Security Information and Event Management (SIEM) reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.