IBM Security QRadar and Splunk User Behavior Analytics are prominent competitors in the security analytics and SIEM landscape. IBM Security QRadar tends to have an edge in scalability, comprehensive reporting, and integration with Watson, making it attractive for larger enterprises.
Features: IBM Security QRadar offers robust log management, scalability, and user behavior analytics. Its integration with Watson and the ability to create customized rules are highly valued. Splunk User Behavior Analytics excels in advanced data correlation, real-time data collection, and offers customizable dashboards, catering to enterprise needs.
Room for Improvement: IBM Security QRadar could improve its installation process, graphical analytics, and vulnerability management. Users also express the need for better API access and seamless integrations. Splunk User Behavior Analytics is criticized for high data ingestion costs and the necessity for better downward integration and automated analytics tools.
Ease of Deployment and Customer Service: IBM Security QRadar provides strong on-premises deployment flexibility with mixed reviews on technical support responsiveness. Splunk User Behavior Analytics receives favorable feedback for customer service but occasionally struggles with support responsiveness.
Pricing and ROI: IBM Security QRadar is viewed as expensive with a complex EPS-based licensing structure but delivers good ROI for its feature set. Splunk User Behavior Analytics is also costly, given its unpredictable data-based pricing. Nonetheless, its extensive features are deemed worth the investment for large-scale data management.
With SOAR, the workflow takes one minute or less to complete the analysis.
Investing this amount was very much worth it for my organization.
The solution can save costs by improving incident resolution times and reducing security incident costs.
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 problem escalates through level one to level three, and then the process starts over with Novo again.
Mission-critical offering a dedicated team, proactive monitoring, and fast resolution.
From the responsiveness perspective, Splunk is very responsive with SLA-bound support for premium tiers.
I would rate the support at eight, meaning there's some room for improvement.
For EPS license, if you increase or exceed the EPS license, you cannot receive events.
Splunk User Behavior Analytics is highly scalable, designed for enterprise scalability, allowing expansion of data ingestion, indexing, and search capabilities as log volumes grow.
I think QRadar is stable and currently satisfies my needs.
The product has been stable so far.
With built-in redundancy across zones and regions, 99.9% uptime is achievable.
Splunk User Behavior Analytics is a one hundred percent stable solution.
Splunk User Behavior Analytics is highly stable and reliable, even in large-scale enterprise environments with high log injection rates.
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.
Global reach allows deployment of apps and services closer to users worldwide, but data sovereignty concerns exist and region selection must align with compliance requirements.
I encountered several issues while trying to create solutions for this advanced version, which seem unrelated to query or data issues.
High data ingestion costs can be an issue, especially for large enterprises, as Splunk charges based on the amount of data processed.
Splunk is more expensive than IBM Security QRadar.
Reserved instances with one or three-year commitments offer lower rates, providing up to 70% savings.
Comparing with the competitors, it's a bit expensive.
The pricing is based on the amount of data processed, and it is considered a high-level investment for enterprises.
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.
We have FortiSOAR and IBM Resilient for IBM Security QRadar orchestration.
I also utilize it for anomaly detection and behavior analysis, particularly using Splunk's machine learning environment.
Features like alerts and auto report generation are valuable.
Splunk User Behavior Analytics offers several beneficial features, such as Insider Threat Detection, account compromise detection, risk scoring, threat detection, and machine anomaly detection.
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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