The Path Towards Modern Cloud Data Warehousing with Snowflake

Picture courtesy: Snowflake Computing Inc.

The Rising Need of a Modern Data Warehouse

  • In the past and present, several organizations have managed their data on-premise where the data sources are present in a local database and bound by network firewalls. More recently, the growing pain of a traditional on-premise data warehouse has led to performance issues, workload contentions, etc. One of the most common outcome is longer run times of user reports that eventually could time out or hang up without completion. Typically, companies have to work around with options like changing the data load processes by building smaller aggregate datasets or separating the conflicting run times for data and dashboards.
  • The rise of new data sources and the growing trend of IoT (Internet of Things) has a huge impact on the analytics. This data being unstructured and huge in volume could pose challenges to design datasets using traditional database practices. This makes cloud data warehouse a perfect location to store and integrate the data.
Picture courtesy: Snowflake Computing Inc.

Storage, Compute, and Services

  • Snowflake uses Amazon S3 for storage. It supports columnar based storage which leads to improved query performance
  • The independent compute resources handle the data processing tasks for loading and running queries
  • The services layer is like the engine that communicates with Client applications to coordinate query processing and return results

Infinite Scalability and Elasticity

Learn more about our partnership with Snowflake

Say Goodbye to Work Load Contentions

Handle Various Data Forms


  • Let’s say an object was deleted accidentally. Do you think it can be recovered to the state it was in at that point of time? The answer is yes. Snowflake offers a retention period up to 90 days to recover the objects that have been deleted.
  • Snowflake allows you to create a secure view when sharing needs to be restricted within a required data set. Snowflake strongly recommends sharing secure views and/or secure UDFs instead of directly sharing tables so that it does not expose all the sensitive data underneath. We can also add privileges to the secure view to other groups.

Keep Reading: Getting Started with Snowflake Cloud Data Warehouse




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