

IBM Security QRadar and OpenText Behavioral Signals are competing products in the cybersecurity analytics space. Through our data comparison, IBM Security QRadar appears stronger in comprehensive analytics and threat detection, while OpenText Behavioral Signals excels in behavioral analysis and natural language processing capabilities.
Features: IBM Security QRadar provides real-time threat intelligence, extensive security tool integration, and robust threat management capabilities, which make it ideal for enterprises. Meanwhile, OpenText Behavioral Signals offers advanced behavioral and sentiment analysis, providing deep insights into human communication patterns to enhance behavioral monitoring.
Room for Improvement: IBM Security QRadar could enhance its user interface to simplify the user experience further. Expanding integration capabilities with non-IBM tools could also be beneficial. Additionally, reducing deployment complexity by offering more streamlined installation options would be an improvement. For OpenText Behavioral Signals, improving integration with a broader range of security tools could enhance its appeal. Enhancing its real-time analytics capabilities and broadening its threat detection features would provide a more comprehensive solution.
Ease of Deployment and Customer Service: IBM Security QRadar benefits from a structured deployment process supported by extensive customer service options, facilitating installation in complex environments. On the other hand, OpenText Behavioral Signals offers streamlined deployments but may require additional customization for broader applications, which showcases its niche capabilities and the need for specialized customer support.
Pricing and ROI: IBM Security QRadar involves a significant upfront investment but promises substantial returns with its powerful threat detection capabilities. OpenText Behavioral Signals offers a more budget-friendly solution with potential high ROI through its unique behavioral insights, particularly valuable in communication-heavy sectors, suggesting that QRadar is better suited for large enterprises prioritizing comprehensive security, while Behavioral Signals provides cost-effective value for organizations focusing on enhanced communication insights.
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.
I have seen a return on investment; I can share that it includes time saved, money saved, and fewer employees needed.
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.
IBM Security QRadar's scalability is great; you can have a new collector to deploy if you have increased EPS per second.
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 | Market Share (%) |
|---|---|
| IBM Security QRadar | 5.6% |
| OpenText Behavioral Signals | 0.7% |
| Other | 93.7% |


| Company Size | Count |
|---|---|
| Small Business | 91 |
| Midsize Enterprise | 39 |
| Large Enterprise | 105 |
IBM Security QRadar (recently acquired by Palo Alto Networks) is a security and analytics platform designed to defend against threats and scale security operations. This is done through integrated visibility, investigation, detection, and response. QRadar empowers security groups with actionable insights into high-priority threats by providing visibility into enterprise security data. Through centralized visibility, security teams and analysts can determine their security stance, which areas pose a potential threat, and which areas are critical. This will help streamline workflows by eliminating the need to pivot between tools.
IBM Security QRadar is built to address a wide range of security issues and can be easily scaled with minimal customization effort required. As data is ingested, QRadar administers automated, real-time security intelligence to swiftly and precisely discover and prioritize threats. The platform will issue alerts with actionable, rich context into developing threats. Security teams and analysts can then rapidly respond to minimize the attackers' strike. The solution will provide a complete view of activity in both cloud-based and on-premise environments as a large amount of data is ingested throughout the enterprise. Additionally, QRadar’s anomaly detection intelligence enables security teams to identify any user behavior changes that could be indicators of potential threats.
IBM QRadar Log Manager
To better help organizations protect themselves against potential security threats, attacks, and breaches, IBM QRadar Log Manager gathers, analyzes, preserves, and reports on security log events using QRadar Sense Analytics. All operating systems and applications, servers, devices, and applications are converted into searchable and actionable intelligent data. QRadar Log Manager then helps organizations meet compliance reporting and monitoring requirements, which can be further upgraded to QRadar SIEM for a more superior level of threat protection.
Some of QRadar Log Manager’s key features include:
Reviews from Real Users
IBM Security QRadar is a solution of choice among users because it provides a complete solution for security teams by integrating network analysis, log management, user behavior analytics, threat intelligence, and AI-powered investigations into a single solution. Users particularly like having a single window into their network and its ability to be used for larger enterprises.
Simon T., a cyber security services operations manager at an aerospace/defense firm, notes, "The most valuable thing about QRadar is that you have a single window into your network, SIEM, network flows, and risk management of your assets. If you use Splunk, for instance, then you still need a full packet capture solution, whereas the full packet capture solution is integrated within QRadar. Its application ecosystem makes it very powerful in terms of doing analysis."
A management executive at a security firm says, "What we like about QRadar and the models that IBM has, is it can go from a small-to-medium enterprise to a larger organization, and it gives you the same value."
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.
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