Microsoft Fabric, Databricks and Snowflake: Collaboration in the world of data

In today’s data landscape, we are witnessing a shift from traditional data platforms towards flexible, open and integrated solutions. During our recent webinar, we explored the interplay between Microsoft Fabric, Databricks, and Snowflake, and how these platforms can complement one another in modern data architectures.

This blog post explains how organisations with varying levels of maturity and technical capability can make the right strategic choices — leveraging the strengths of each platform to build open, future-proof data ecosystems.

An open and integrated approach

The core message was that Microsoft Fabric should not be seen as a competing alternative, but rather as a complement to existing investments in platforms such as Databricks and Snowflake. The aim is to position Fabric as an open product that respects and integrates with customers' current technology stack.

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This means that the “source of truth” in Fabric – the so-called OneLake using Delta tables – forms an open, ACID-compliant storage layer. Thanks to this approach, organisations can manage and move their data to other systems if needed, avoiding vendor lock-in.

Different layers and use cases

A key discussion point was the layering of data architectures. Often, the “source layers” (the bronze and silver layers) are still managed in Databricks or Snowflake, while the “gold layer” resides in Fabric. This model illustrates how organisations can migrate in phases and benefit from both technical strength and self-service reporting capabilities.

For companies with large, technically skilled data engineering teams, a combination of powerful platforms like Databricks or Snowflake with the simplicity and openness of Microsoft Fabric appears to be the most logical choice. Conversely, organisations with less technical teams, who prefer a SaaS solution, may be more drawn to Fabric's self-service and user-friendly features.

Open architecture as a key strength

One of Fabric’s major advantages is its open nature. All data is centrally stored as Delta tables (which are essentially Parquet files with a transaction log), ensuring seamless integration with other technologies. New features – such as support for competing formats like Iceberg – ensure that Fabric continues to evolve and remains relevant for both current and future investments.

The open architecture allows organisations to leverage investments in Databricks via Fabric, and vice versa. This means they are not forced to choose one single platform, but can embrace a “both-and” scenario where multiple technologies coexist and complement one another.

Conclusion: A future of collaboration

The discussion clearly showed that there is no single answer to the question of which platform is “better.” It strongly depends on an organisation’s maturity, technical capabilities and specific needs. What is evident, however, is that Fabric takes a significant step in avoiding vendor lock-in by adopting an open and integrated approach. This enables organisations to build flexible, future-proof data ecosystems without having to compromise on technical functionality or user experience.

Whether it's organisations already heavily invested in Databricks or Snowflake, or those still operating legacy on-premise stacks – the evolution towards an open and collaborative data architecture offers something for everyone. Success lies in the ability to combine the strengths of each platform, allowing customers to fully benefit from the opportunities the modern data world has to offer.

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Have questions about Microsoft Fabric or do you want to explore how Microsoft Fabric can help your team deliver reliable, governed data products?

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