See how the open, governed security lakehouse unifies security, IT, and business data to power modern SOCs
by Andrew Krioukov, Jack Naglieri, Taylor Kain and Dave Herrald
Today, we are thrilled to announce that Databricks has officially completed the acquisition of Panther, an AI SOC platform built for modern security operations. Cybersecurity has fundamentally transformed into a data management and AI problem. The ability to collect, retain, and analyze data at scale and in real time is now the limiting factor in how fast a SOC can detect and respond. Attackers are leveraging automation and AI to move faster, hide within massive volumes of complex data, and launch increasingly sophisticated, multi-stage attacks across cloud, identity, and SaaS environments. To defend modern enterprises, security teams require an architecture capable of processing petabytes of telemetry with continuous context and automated intelligence.
Legacy SIEMs were built more than a decade ago around limited data ingestion, strict sampling trade-offs, rigid compute architectures, and manual alert triage. Constrained by high compute costs and inflexible processing power, this legacy approach simply cannot scale to defend against AI-driven threats and rapid zero-day attacks. The industry needs a new paradigm. Databricks established that paradigm with the security lakehouse: an open, governed lakehouse that unifies security, IT, and business data in one place so SOC teams can run detection, investigation, and response directly on top of that data.
