Security Analytics

It is a long established fact that cybersecurity has become a Big Data problem. With a constantly evolving threat landscape, security professionals must increase both the sophistication, and speed in which they can respond to these threats.

Read the Bigstream whitepaper to understand how Hyper-acceleration of security analytics workloads happens without changing your code

Cybersecurity also presents the dual challenge of low-latency detection and remediation of advanced threats, and batch analysis of log data from servers, firewalls, applications and security systems. Considering how fast new threats and attacks emerge, Big Data performance and the use of new types of software and hardware accelerators is becoming more critical.

With security analytics workloads requiring both low latency response times for interactive queries as well as batch processing for deeper analytics and compliance, Bigstream Hyper-acceleration provides a performance boost for both types of workloads.

Some of the specific examples of Hyper-acceleration of the security analytics pipeline include:

  • High-performance processing of network and security events
  • Real-time correlation of input events with users and network resources
  • High-performance Machine Learning for anomaly detection and user behavior categorization

Bigstream benchmark testing shows 4X or better acceleration of ingest, compress/decompression, data and document parsing, and Spark SQL analytics.

Read the Bigstream Benchmark Report to see how Bigstream Hyper-acceleration will transform your Big Data security analytics.