Gartner Publishes 2013 Magic Quadrant for Security Information and Event Management (SIEM)
Just as surely as spring has established a foothold on Cape Cod, the SIEM Magic Quadrant for 2013 has published. The news is out, and IBM Security has improved our position as a Leader in the 2013 Magic Quadrant for SIEM (Security Information and Event Management) again — marking the 5th year in a row that IBM Security/Q1 Labs has achieved this leadership position. For the first time, IBM/Q1 Labs is in the top position in the SIEM MQ.
IBM/Q1 Labs also received outstanding scores and improved standings in the 2013 SIEM Critical Capabilities report, which provides numerical ratings of vendors by capability and use case.
Back to bragging: IBM Security (Q1 Labs) is rated #1 (above every other vendor) on “Ability to Execute” (the Y-axis). This represents overall viability, product/service, customer experience, market responsiveness, product track record, sales execution, operations and marketing execution.
- IBM/Q1 Labs is rated above major competitors (McAfee/Nitro, Splunk, LogRhythm, and RSA) on both “Ability to Execute” and “Completeness of Vision” (the X-axis). Completeness of Vision represents product strategy, innovation, market understanding, geographic strategy, and other factors.
- IBM/Q1 Labs is rated highest in the Critical Capabilities report for essential elements of Security Intelligence with Big Data: Analytics and Behavior profiling
- IBM/Q1 Labs is the highest rated in the SIEM Use Case, Product Rating, and Overall Use Case categories.
Besides vendor chest-thumping, what does this mean to our customers? Simply this: the creation and development of the IBM Security Systems division concurrent with the acquisition of Q1 Labs ensured:
- Customer-facing focus
- Continued and increased investments in Security Intelligence
- More opportunities to engage with more customers worldwide
- More 3rd party partnerships to ensure Big Data collection from more and more sources
- Resources unique to IBM. And face it, no one knows data like IBM.