The Data Stack Show 47: Taming the Four Dragons of Data with Sven Balnojan of Mercateo Gruppe
Aug 4, 2021
Sven Balnojan, a PhD in Singularity Theory, shares his insights as a writer and product manager in the data realm. He dives into the dynamics between Databricks and Snowflake, highlighting their distinct approaches to structured and unstructured data. The conversation also tackles the challenges of innovating and making technology accessible, as well as the critical need for organizational change in response to emerging tech. Additionally, Sven discusses the complexities of successful open-source projects and the importance of iterative development.
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Sven's Diverse Data Path
- Sven's journey started with a failed startup attempt and a PhD in singularity theory.
- He transitioned through roles from data scientist to product owner in data teams.
Databricks vs Snowflake Origins
- Databricks originates from Apache Spark and works well with unstructured data, while Snowflake started with structured cloud data warehousing.
- Both companies now tackle four forces: data amount, kind, decentralization, and unique company data complexity (snowflake problem).
Technical Comparison of Platforms
- Snowflake revolutionized cloud data warehousing with compute-storage separation and easy management.
- Databricks started harder with Spark but is ambitiously adding database-like features to unify data processing and analytics.