Reduce data duplication and enhance performance by enabling shared access to data across Snowflake, Databricks, and Microsoft Fabric.
I’ve just published a new article exploring strategies to unify data sharing across Snowflake, Databricks, and Microsoft Fabric. While consolidating onto a single platform is often ideal, the reality for many large enterprises is more complex. Team autonomy, legacy investments, and strategic diversification often lead to multi-cloud and multi-product environments. Can your cross-platform integration architecture become a strategic advantage? The full article focuses on options to share delta parquet and iceberg format storage amongst the three platforms:
In the real world, very few large organizations are unified on a single data and analytics platform. Snowflake, Databricks, and Microsoft Fabric are all very popular products with widespread adoption. All three offer lakehouse architecture tools, but what are your options if you have data in more than one of these products? How do you share data amongst the platforms in a way that minimizes replication, is cost efficient, and has low latency?
This post is the first in a three part series focusing on interoperability amongst Snowflake, Databricks, and Microsoft Fabric. The following list will be updated with urls as the posts are published:
- Unify data sharing across Snowflake, Databricks, and Fabric for a lakehouse trifecta (this article)
- Snowflake and Microsoft Fabric integration connectivity options (coming soon)
- Databricks and Microsoft Fabric integration connectivity options (coming soon)
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