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Data Warehouse

Snowflake on Google Cloud – Pandera Partners Unite

Snowflake, the data warehouse built for the cloud, announced at their Snowflake Summit on June 4th the expansion of their product offering to integrate with Google Cloud Platform. As data warehouses of the past strain under the increasing burden of extremely large and diverse data sets as well as storage and compute resources necessary to process and analyze the data within them, Snowlake attacks those problems head on. Through their cloud-built data warehouses, Snowflake, enables seamless and secure data integration throughout organizations across its platforms and multiple cloud environments. Modern Data Warehouse architecture built for the cloud provides access to near infinite, low-cost storage; improved scalability; the outsourcing of data warehousing management and security to cloud vendor; and the potential to personalize payment to reflect only the storage and computing resources actually used from day to day.

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Snowflake for Data Science

Anyone working on a cloud-friendly data science, data engineering, or data warehousing team has surely heard the name Snowflake come up over the past couple of years.

For those that haven’t, Snowflake is a relatively new database solution that is majorly innovative in some ways and yet simultaneously familiar in the ways that matter.

The product is essentially a SaaS database built with cloud-native features that we 21st century data enthusiasts (fine… nerds) have come to expect from off-the-shelf products. Some of these features include:

  • the ability to quickly and automatically scale computing power — responding to highly variable workloads in a way that enables high velocity data to flow in, unimpeded by ingestion bottlenecks
  • the separation of storage and compute, both technically and on billing statements — making cold data retention much more cost-effective
  • the ability to segregate and securely share chunks of data — reducing the amount of maintenance and management that data ops teams need to invest in shared data assets
  • automatic query and data optimization — this one speaks for itself!

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