Data Vault on Snowflake: Dynamic Information Marts

Snowflake continues to set the standard for Data in the Cloud by taking away the need to perform maintenance tasks on your data platform and giving you the freedom to choose your data model methodology for the cloud. You will expect the same relational capabilities for your data model as any other platform and Snowflake certainly delivers.

Announced at Snowflake Summit 2022, Dynamic Tables is the next level table type optimised for real-time streaming transformation. Dynamic Tables behave like Materialised Views but are really the declarative version of Streams and Tasks (introduced back in 2019) where Snowflake manages the data pipelines on your behalf. That said, Dynamic Tables can be used for batched workloads, combining batch and near-time streaming and solely for real-time streaming transformations. What’s more is that Dynamic Tables can be stacked into a direct acyclic graph (DAG) and you do not need to manage the underlying streams and tasks deployed on your behalf.

Does it replace Streams and Tasks? No, where you desire more control over how the offsets work for your data pipelines you would likely choose Streams and Tasks over Dynamic Tables. We covered some of this in this Streams on Views article.

It is an exciting bit of Snowflake technology, many have already asked, “where can Dynamic Tables be…