Snowflake, Databricks, and Federated IT strategies prioritize open catalogs, interoperability, and vendor-agnostic architectures for scalable, secure data access.
Organizations have been locked in an ongoing debate over whether Snowflake or Databricks provides the superior Cloud Data Platform. Both companies have developed impressive ecosystems, offering Data Analytics, AI capabilities, and Data Management solutions. However, these platforms often require organizations to move or transform large volumes of Big Data into proprietary storage or specific formats, which leads to concerns about vendor lock-in and operational rigidity.
The Reality of Enterprise Data: It’s Everywhere
No matter how compelling Snowflake and Databricks’ offerings may be, organizations will always have Big Data residing in disparate locations. This is because enterprise data exists across on-premises databases and legacy Data Warehousing, cloud object storage in multiple formats (Parquet, Avro, ORC, etc.), modern data lakes leveraging open standards, and third-party data sources shared via APIs or external storage.
The Future: Federated IT and Portable Data Catalogs
Rather than engaging in the Snowflake vs. Databricks debate, forward-thinking organizations want a Federated IT strategy. This IT Shift embraces the diversity of Cloud Data Platforms and processing solutions while ensuring seamless access and governance across the enterprise. At the heart of this transformation is the evolution of open and portable data catalogs.
A modern data catalog is not just a metadata repository; it serves as the backbone of Federated IT access. It provides a unified view of data in the data lakehouse and governance and security policies that apply consistently regardless of where the data resides and is processed. Better yet, it offers interoperability with multiple query engines, enabling teams to use the best tool for their needs without migrating Big Data.
Delivering Data for BI and AI with Flexibility
The war between Snowflake and Databricks ultimately distracts organizations from the real goal: enabling teams to curate, govern, and deliver data flexibly and efficiently. Instead of focusing on which vendor offers the best solution, organizations should prioritize:
A Federated IT strategy that allows for diverse Cloud Data Platforms and processing engines.
Interoperability across cloud and on-premises environments.
A single, portable catalog layer that abstracts the complexity of multiple storage formats and query engines.
Self-service capabilities for BI and AI teams, ensuring they can access trusted data without relying on centralized Enterprise IT bottlenecks.
The Role of Data Products in a Federated IT Platform
Beyond simply unifying data, a Federated IT platform enables organizations to transform unified data into data products. Data products are governed, curated, and accessible datasets – or groups of datasets – managed with clear accountability, similar to how a product manager oversees traditional projects. These data products ensure that teams across the organization can rely on consistent, high-quality, and well-governed data for their specific use cases, whether for BI, AI, or operational analytics.
A federated approach to Enterprise IT should facilitate the creation and management of data products by enforcing governance policies that ensure data integrity, security, and compliance, and by providing self-service data access with clear ownership and documentation. It also supports multiple storage formats and processing engines to cater to diverse needs and delivers an abstraction layer that enables Cloud Data Platforms and Data Analytics products to be consumed in a unified manner across different tools and platforms.
The Unanswered Question: How Will Federated Data Product Delivery Work?
While the industry is moving toward a federated model for Federated IT and data product management, an open and critical question remains: how can this be implemented at scale? Over the next few years, organizations and vendors will grapple with key challenges to address this by:
Open Table Formats & Lakehouse Catalogs: The Building Blocks of Federated Data
The companies developing and pitching their version of this future are making their play for dominance in the evolving Cloud Data Platforms landscape. Organizations must carefully evaluate these offerings and prioritize open, flexible solutions that align with their long-term IT Shift strategy.
Moving on from the Snowflake/Databricks dilemma: Embrace Federated IT & It Won’t Matter
Rather than getting caught up in the battle between Snowflake and Databricks, organizations should recognize that the future of Enterprise IT architecture is neither platform-specific nor proprietary. The real opportunity lies in federated governance, interoperability, and a unified catalog layer that enables seamless Data Analytics and management across diverse environments.
By embracing open standards and leveraging portable catalogs like Apache Polaris and Unity Catalog, businesses can future-proof their Data Warehousing and overall Cloud Data Platforms strategy. This IT Shift also allows for greater flexibility, improved collaboration, and an architecture that supports BI, AI, and other emerging workloads without compromising governance or control. In the end, organizations don’t need to choose a winner in the Snowflake vs. Databricks war—they need a Federated IT strategy that transcends it.
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