Bringing the power of Databolt directly to Snowflake

Many enterprises today have a dual mandate of maintaining the highest levels of data security to protect their customers’ data, while at the same time using data to drive innovation and deliver new products and services. To address this problem at Capital One, we turned to data tokenization to meet the speed, scalability and security requirements of our organization while maintaining data usability for machine learning, analytics and AI. 

This investment in technology eventually led to the creation of Capital One Databolt, a data tokenization solution from Capital One Software. Databolt allows users to secure data using generic APIs and SDKs to tokenize and detokenize information across their organization. At the same time, the modern data ecosystem is large, complex and ever-changing. For both security and efficiency, it often makes sense to have tools built directly into, or optimized for, the stack that your data teams use every day. 

For many modern organizations, Snowflake is a major part of that data stack. Because of this, we built a Snowflake integration that brings Databolt directly into the Snowflake ecosystem. Partnering closely with the Snowflake team, we are bringing seamless, enterprise-grade tokenization directly to Snowflake users via our Databolt product. Snowflake users can now tokenize and detokenize sensitive data without having it ever leave their Snowflake environment. By bringing tokenization directly to Snowflake data, this partnership unlocks new opportunities and use cases for Snowflake customers in the areas of advanced analytics, data sharing and AI. 

• Built for Snowflake data: Databolt has been optimized to handle the data output formats of the Snowflake ecosystem to meet enterprise performance needs.

• Leverages Snowflake infrastructure: Databolt for Snowflake takes advantage of some of Snowflake’s most powerful new tools, such as Snowpark Container Services (SPCS) to deploy its tokenization engine directly where your data lives, decreasing latency and removing the need to unnecessarily cross trust boundaries.

• Snowflake Marketplace + Native App: Databolt for Snowflake has been packaged for consumption completely within the Snowflake ecosystem. In addition to leveraging infrastructure like SPCS, there is a Snowflake Native Application that you can download through the Snowflake Marketplace to simplify onboarding, installation and setup of tokenization.

• Flexible deployment model: Snowflake-native deployments on SPCS can easily work hand-in-hand with deployments across a wider technical ecosystem.

• Built on Snowflake RBAC: Databolt for Snowflake builds access to tokenize and de-tokenize information directly on top of Snowflake’s Role infrastructure, to minimize the amount of time it takes to onboard new teams and use cases.

• Direct delivery of UDFs: The Native App will install UDFs that users can leverage in their Snowflake environment to interact with tokenization and de-tokenization functionality. 

• Secure data analytics and AI-ready data: Databolt tokens maintain referential integrity, ensuring utility of tokenized data for analytics, machine learning and AI without exposing sensitive information to data consumers, data users and data scientists.

• Containerized application: Databolt is designed to scale both vertically and horizontally to take advantage of cloud technologies like Kubernetes.

Getting started with Databolt for Snowflake is a streamlined process thanks to the Snowflake Marketplace. Users can find the Databolt product listing on the Snowflake Marketplace and simply leverage the Native App to start the installation process in their Snowflake environment.

As businesses adopt AI at scale, the ability to secure data without compromising utility becomes critical. Together with Snowflake, we’re making that a reality. Visit our product page to learn more about Databolt and schedule a demo.