Why cloud-native data warehousing instead of the traditional on-premises breed? Because the later fits like a square peg in the cloud’s round hole of unlimited scalability and elasticity, according to Michael Nixon (pictured, left), senior director of product marketing at Snowflake Computing Inc.

What makes Snowflake’s infrastructure unique is how it slices compute, storage and service into three separate layers, according to Nixon. “And that’s really important, because … you want unlimited capacity, unlimited resources,” he said.

The old warehousing methods like massively parallel processing databases made scaling an arduous tag-along of uncalled for stuffs, he explained. The storage and compute are attached at the hip, so to speak, and can’t be scaled independently. “So when you scale the storage along with the compute, usually that involves a lot of burden on the data warehouse manager, because now they have to redistribute the data and that means redistributing keys,” Nixon stated. Snowflake users can scale individual layers with pure usage-based pricing. 

Nixon, along with Snowflake user David Abercrombie (pictured, right), senior staff engineer at Sharethrough Inc., spoke with George Gilbert (@ggilbert41), host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, at the BigData SV event in San Jose, California. They discussed how cloud data warehousing cuts costs and lifts burdens on data analysts.

Have a three-layer cake and analyze data too

Aside from bringing sanity to scaling, Snowflake scalpels out some pains of data analysis and business intelligence, Abercrombie explained. Sharethrough is a native advertising software and ad exchange.

“At the core of our business we run an ad exchange, where we’re doing programmatic training with the bids, with the real-time bidding spec,” he said. It deals in super high-volume data — 12 million impressions per month.

The company uses JavaScript Object Notation, or JSON, a lightweight data-interchange format, which is, for better and for worse, richly complex, Abercrombie stated. Snowflake plows through some of this complexity, so analysts don’t have to.

“We sort of have our cake and eat it too,” Abercrombie said. “We can have our JSONs with their full richness in our database, but yet we can simplify and expose the data elements that are needed for analysis, so that an analyst — their first day on the job — they can get right to work and start writing queries.” 

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the BigData SV event. 

Photo: SiliconANGLE