I am thrilled to announce that Hunters SOC Platform is now available for Databricks customers, helping them move beyond SIEM and consolidate their data in a modern, cloud-based data lake for better cost and security outcomes.

For the first time, Databricks customers will be able to attain an end-to-end security operations platform with their security data stored in their own Databricks Lakehouse deployments, keeping the flexibility of owning all data and the power to build their own security use cases on the Lakehouse.

At Hunters, we’re committed to the premise that data storage and analytics should be decoupled. Cybersecurity is a big data problem, and yet security teams shouldn’t be spending their time working on data engineering problems like ingestion and preparing the data for security analytics. 

The security market has been conditioned to expect that more data means more people, time, and costs to address threats. Hunters shifts that paradigm by leveraging the leading modern data platforms and their powerful scale and cost efficiencies, and a commercial model that separates storage from compute. Security teams shouldn’t be forced to make the hard decision of what data to store and for how long, but rather have it all readily available without taxing the security budget.

By integrating with leading data-focused technologies like the Databricks Lakehouse, we are enabling our customers to gain deeper insights into their organization's security and respond to threats more quickly and effectively, bringing their security data lake of choice. For Databricks customers leveraging it in other parts of the business, this offers an opportunity for consolidation and storage of security data under the same Lakehouse.

This is another step on our journey to revolutionize security analytics that began over three years ago when we first partnered with Snowflake, and ever since we’ve empowered customers to bring their own data lake or use Hunters’ hosted one to run their security operations on.

Special thanks to our partners at Databricks, and massive kudos to the product and R&D teams behind this massive engineering undertaking.