IBM Security QRadar and Splunk User Behavior Analytics are prominent contenders in the security information and event management (SIEM) category. IBM Security QRadar seems to have the upper hand due to its comprehensive suite of features and all-in-one security platform capabilities.
Features: IBM Security QRadar offers streamlined log management, scalability, and easy integration with third-party solutions. It serves compliance requirements efficiently and provides advanced correlation and alerting capabilities. Splunk User Behavior Analytics focuses on anomaly detection and behavior analysis, utilizing a machine learning environment. It excels at data querying and indexing, making it a strong option for real-time data analysis.
Room for Improvement: IBM Security QRadar could enhance its graphing and analytics capabilities and improve technical support response times. Its complex and costly licensing is also a concern for users. Splunk User Behavior Analytics faces criticism for high pricing and a complex licensing structure. Users recommend improving persistent rule correlation and enhancing third-party tool integration.
Ease of Deployment and Customer Service: IBM Security QRadar supports on-premises and hybrid cloud deployments with a robust support team, although support quality can vary by region. Splunk User Behavior Analytics is available both on-premises and in the cloud, offering strong customer service; however, users sometimes rely on professional services for optimal setup.
Pricing and ROI: IBM Security QRadar is high-priced with complex EPS-linked licensing, making it less suitable for small businesses but providing solid ROI for larger enterprises. Splunk User Behavior Analytics also encounters pricing challenges with unpredictable costs for integrations, yet both tools are noted for delivering substantial ROI in enterprise environments.
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.
The problem escalates through level one to level three, and then the process starts over with Novo again.
I received very good support, possibly due to a good relationship with IBM.
I would rate the support at eight, meaning there's some room for improvement.
The product has been stable so far.
I think QRadar is stable and currently satisfies my needs.
Splunk User Behavior Analytics is a one hundred percent stable solution.
If AI-related support can suggest rules and integrate with existing security devices like MD, IPS, this SIM can create more relevant rules.
We receive logs from different types of devices and need a way to correlate them effectively.
Improving the integration with IBM Server for MetaMask for correlation rules would be beneficial.
Advanced reporting could see enhancements as there are some issues with latency.
Recently, I faced an incident, a cyber incident, and it was detected in real time.
IBM is seeking information about IBM QRadar because a part of QRadar, especially in the cloud, has been sold to Palo Alto.
I also utilize it for anomaly detection and behavior analysis, particularly using Splunk's machine learning environment.
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."
Splunk User Behavior Analytics is a behavior-based threat detection is based on machine learning methodologies that require no signatures or human analysis, enabling multi-entity behavior profiling and peer group analytics for users, devices, service accounts and applications. It detects insider threats and external attacks using out-of-the-box purpose-built that helps organizations find known, unknown and hidden threats, but extensible unsupervised machine learning (ML) algorithms, provides context around the threat via ML driven anomaly correlation and visual mapping of stitched anomalies over various phases of the attack lifecycle (Kill-Chain View). It uses a data science driven approach that produces actionable results with risk ratings and supporting evidence that increases SOC efficiency and supports bi-directional integration with Splunk Enterprise for data ingestion and correlation and with Splunk Enterprise Security for incident scoping, workflow management and automated response. The result is automated, accurate threat and anomaly detection.
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