To Snowflake or not to Snowflake


To Snowflake or not to Snowflake

Snowflake has made a grand entrance in the market. Are all key elements they promote as disruptive as suggested?

By Kevin Kewal, Jeannine de Kuijper, and Jeroen Gelderblom

Through this article, we present the most well-known Snowflake components and discuss their capabilities. Who knows, this might just be the information you need to decide on whether or not you should transition to Snowflake.

Since the launch of the Snowflake Partner Network (SPN), Deloitte has been the fastest organization to achieve Snowflake’s top level of recognition as an Elite Services Partner. With over 500.000 hours of hands-on Snowflake implementation experience, Deloitte has a track-record of delivering analytic modernization projects for its clients and has demonstrated capabilities, comprehensive approaches and accelerators. Recently, Snowflake has gradually climbed its way up the Gartner Magic Quadrant, into the Leader and Visionary quadrant. So, what makes Snowflake so special? Why is it becoming such a hot topic despite its cold name? 

Deloitte’s collaboration with Snowflake and its experience in migration projects for clients have given us an insight into the benefits and drawbacks of implementing such a system. In this article we lay out the unique Snowflake architecture and dive deeper into a few of the core topics: separation of storage and computation along with the costs, automatic scaling, zero-copy cloning, semi-structured and schema-less data support, data protection, data owners, and third parties. Our experience with these Snowflake areas enables us to provide the advantages and drawbacks of each and can guide the decision for why a company should or should not transition to Snowflake.

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