Snowflake Unveils Data Cloud Ecosystem for Data Sharing

Snowflake has unveiled its “Data Cloud” ecosystem to break down data silos, derive insights, and deliver value from their data in new and seamless ways. Essentially a way for its users to share and exchange data, Data Cloud will provide more opportunities around data and help break through data silos, says Snowflake.

Snowflake Data Cloud

The Data Cloud is a new type of cloud, explained Snowflake CEO, Frank Slootman, in a blog post. Built on the Snowflake Cloud Data Platform, Data Cloud allows customers to instantly share live data in a governed and secured fashion.

This allows for frictionless data with no copying or replication of data. To use it, customers simply designate data for sharing and grant the appropriate permissions. Recipients can then process against data in place, without ever gaining physical custody of that data. The result is data that is always up to date; updates to shared data sets by the providers are instantly available to their customers.

“Organizations have historically struggled to fully mobilize data in the service of their business,” Slootman said. “Snowflake was specifically architected to leverage the incredible scale and computing power of the cloud. As part of the Data Cloud, organizations fully mobilize their data by blending and joining data with broader context, giving them the power to achieve crucial insights beyond what has previously been possible.”

Snowflake’s SVP of Product, Christian Kleinerman noted that the feature enhancements will help companies unify, integrate, analyze, and eliminate the complexity and friction of alternative solutions. Businesses can join a global ecosystem of data consumers, providers, and service providers to share “virtually” any amount of data.

New features

Snowflake also took the opportunity to announce new features for its Snowflake Cloud Data Platform. Some of the most notable ones in public preview are:

• Snowsight: A new analyst experience within Snowflake to execute queries and commands with visualization and dashboards for a streamlined experience.
• Search Optimization Service: Dramatically improved performance for point lookup queries on large tables of data.
•  External Functions: Use Snowflake to call external services for richer query support and to build robust data pipelines that integrate with third-party libraries or services.

To understand more about Snowflake and why data scientists can benefit from building a data warehouse in the cloud, check out our interview with Geoff Soon, the managing director of Snowflake in South Asia here.

Photo credit: iStockphoto/Jirsak