With the launch of this bi-directional integration, users can leverage the unique strengths of SingleStore with their data stored in Snowflake, without having to exfiltrate that data. Ultimately, this serves to reduce complexity and better streamline enterprise’s data storage, according to Rahul Rastogi, CIO of SingleStore.

“I’m very excited that Snowflake users will now be able access key elements of SingleStore’s data platform natively in Snowflake,” Rastogi continued. “This will allow them to continue to store all their data in one single place, instead of having to plug in an external independent system, which usually results in increased complexity, labor, and licensing costs. Working with Snowflake to make this a reality shows our mutual commitment to help customers build better real-time AI applications.”

This integration also allows customers to use hybrid search with semantic and exact keyword matching capabilities to query data across multiple data types—including JSON. For those looking to incorporate additional real-time analytics features for apps built on Snowflake, they can now mix streaming data with data in Iceberg format.

“We are thrilled to combine our capacities with Snowflake’s to fulfill developers’ needs to build smart data and AI apps natively in Snowflake,” said Nadeem Ashgar, head of engineering at SingleStore. “These new capabilities demonstrate that we continue to innovate to offer AI developers the best tools to feed their applications with the fastest and most reliable data.”

“This collaboration underscores SingleStore and Snowflake’s joint commitment to providing users with the most advanced tools available to seamlessly develop AI applications where their data lives,” said Jeff Hollan, head of applications and developer platform at Snowflake. “By bringing SingleStore’s real-time data capabilities within Snowflake, we’re making it easier for customers to build a broader set of workloads.”