Snowflake Tutorial Next Steps

Overview

In this tutorial, we went through the basic features of Snowflake, a cloud-only data warehouse provider. We saw that it brought some innovations to the table, such as instantaneously scalable compute warehouses, time travel for every table and a couple of SQL syntax features which SQL Server might be jealous of. Some of those features have made it into Microsoft Fabric, such as the capacities (which are also resizable in just a few seconds) and time travel.

More

But of course, there’s much more. We did not cover more advanced features of Snowflake, such as security and authorization, data sharing, stored procedures, functions, AI & ML, and so on. The Snowflake website has good documentation on all of these features, there are learning tracks for on-demand training and there is also certification.

Even though Snowflake is easy to work with and has some exciting features, there are also a couple of downsides:

  • The community around Snowflake is quite small and not as vivid as the SQL Server community, but it seems to grow rapidly.
  • The app ecosystem around Snowflake can also use some growth. If you’re used to working with SQL Server, you’re kind of spoiled. We have SSMS, Azure Data Studio, multiple vendors that support automating back-ups, database devops, source control, schema compare and so on. With Snowflake, this ecosystem is much smaller and, in some areas, even non-existing. Chances are you might have to build something yourself. In the last years, tools like dbt and matillion made it easier to work with Snowflake.
  • Snowflake is zero-management, but also zero options. There are no indexes you can create, no primary keys or foreign keys enforcement (you can create them but they are not checked), no query hints et cetera.

As mentioned, Snowflake is quite young so we can expect to see growth in those areas. Snowflake is an interesting product which certainly shows lots of promise.

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