Snowflake offers cybersecurity data platform with security app integrations

In conjunction with third-party security vendors, Snowflake has launched what it calls a “cybersecurity workload” to enhance the capabilities of its data cloud for organizations looing to more  efficiently detect and respond to cyberthreats.

The Snowflake Cybersecurity workload is designed to let enterprises use the company’s namesake data cloud to unify security data from diverse security applications, combining it with contextual data from HR systems or IT asset inventories, according to the company.

The idea, according to Snowflake, is that cybersecurity personnel can then run fast queries against the unified data sets, which can be used to enhance threat detection and investigation, generating higher fidelity alerts.

Snowflake’s new security workload capabilities are aimed at helping security teams break down data silos to enable consistent visibility, eliminate manual processes and improve analytics, according to Omer Singer, head of cybersecurity strategy at Snowflake.

Cybersecurity workload processes data with SQL, Python

Snowflake’s pitch to cybersecurity professionals is that traditional security architectures with legacy SIEM (security information and event management) products are buckling under the strain of handling the volume and variety of data necessary to combat modern cyberthreats. Traditional SIEMs have high ingest costs, limited retention windows and proprietary query languages, all complicating security team’s efforts at visibility and protection.

Snowflake’s cybersecurity workload offers cloud-native capabilities to handle structured, semistructured, and unstructured logs, enabling users to efficiently store years of high-volume data. The platform also boasts a scalable, on-demand compute resource that will allow for searching and gaining insights using languages like SQL and Python. (This capability is currently in private preview.)

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