Optimize connectivity costs, performance, and governance
Back in September I posted on lakehouse integration options between Snowflake, Databricks, and Fabric. You can read that post by clicking here. Many large healthcare companies have multiple platforms in their ecosystems, and optimizing the connectivity amongst those platforms is a strategic benefit. To take a deeper dive, I've published a new post that covers connectivity and integration options between Snowflake and Fabric.
When should you use Power BI or Fabric AI Data Agent Direct Query Mode to Snowflake? What about Fabric Mirroring? Can you get Fabric Real-Time Intelligence data into Snowflake as the cold path of your IoT lambda architecture? The connectivity options between Snowflake and Fabric can be seen below:
Note that I'm not comparing Snowflake and Fabric, but rather covering options for sharing data between the platforms. Realistically, many organizations use both Snowflake and Fabric (+ Power BI) and the tools can be better together with the right connectivity and interoperability options.
For example, Option 2 from the diagram above (Fabric Mirroring of Snowflake) can be illustrated as follows:
With a large Power BI environment or numerous AI Data Agents, queries between Snowflake and Fabric / Power BI can be complex with extremely high concurrency. Even for Import Mode Semantic Models using the Snowflake SQL endpoint, numerous semantic models refreshing frequently can result in high compute costs and duplicate data moving across networks. Fabric OneLake has a capability called Mirroring which can be used to optimize costs and query performance when connecting to Snowflake. Mirroring will connect to a Snowflake table change data capture (CDC) mechanism to pull updates into OneLake as incrementally updated delta parquet tables. Fabric / Power BI tools and reports can then query the copy of the table which has been moved over the network from Snowflake once, opposed to each query crossing the network separately. The Fabric compute and storage costs for Mirroring are also free up to limits described at this link.
The full article, which takes a deep dive into all seven options, can be found at this link: Snowflake, Fabric and Power BI Integration Options – Greg Beaumont's Data & Analytics Blog
Microsoft