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Databricks sued for AI patent infringement dispute ⚖️

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Snowpark enables autonomous data workflows with best practices ❄️

Also, check out the weekly Deep Dive - Fundamentals and Architectures of Databases

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DEEP DIVE

Fundamental Database Concepts and Architectures

I had a meeting about a week ago with a very talented and skilled Associate Director at work. We were discussing some migration plans. I brought up DTS packages and I had to explain that they were the progenitor of SSIS.

I have from that point, realized that I have been working with this data stuff for a very long time and also, I based my career on these fundamental database concepts. The following seem so far removed from the myriad database types and the ancillary platforms and software that surround them now in 2026.

I just want to share some of the concepts that serve as the grounding for my career and perhaps yours (You will notice a skew towards relational databases):

Declarative Referential Integrity

In the modern stack, DRI is the bedrock of automated data consistency, ensuring that relationships between tables remain intact through system-enforced primary and foreign key constraints. While some distributed systems trade this off for performance, maintaining these rules at the schema level prevents orphaned records and preserves the structural integrity required for complex data orchestration.

The Sybase/Microsoft split

The Sybase/Microsoft split in the early ‘90s is one of the most underrated fork-in-the-road moments in database history. What started as a joint effort ultimately led to two divergent paths: Sybase doubling down on enterprise data systems, while Microsoft evolved SQL Server into a dominant force in the Windows ecosystem. Fast forward to today, and you can trace a direct line from that split to Microsoft’s modern data stack—Azure SQL, Fabric, and beyond.

Third Normal Form

Third Normal Form is the backbone of relational data modeling, designed to eliminate redundancy and ensure data dependencies make logical sense. It forces you to think rigorously about how attributes relate to keys—removing transitive dependencies and tightening the structure of your data model. While modern analytics platforms often favor denormalization, 3NF remains critical for transactional systems where consistency and integrity are non-negotiable.

Star Schema and Snowflake Schema

These dimensional modeling patterns are the engines behind modern analytical processing, with the Star Schema prioritizing query simplicity and the Snowflake Schema focusing on normalized efficiency. Choosing between them is a strategic decision in lakehouse architecture, balancing the need for rapid join performance against the benefits of reduced data storage and structural clarity.

Transaction Isolation Levels

Isolation levels define the critical balance between data consistency and system concurrency, determining how changes made by one operation are visible to others. From "Read Uncommitted" to "Serializable," understanding these settings is vital for architects who must prevent anomalies like "dirty reads" or "phantoms" in high-throughput database environments.

E.F. Codd

E.F. Codd is the intellectual architect behind the relational model, and by extension, the entire modern database ecosystem. His work at IBM in the 1970s introduced the idea that data should be organized mathematically—through relations, tuples, and sets—rather than hierarchical or procedural structures. Decades later, every SQL query, every data warehouse, and every normalization rule traces back to his original vision.

Set Theory

At its core, every relational database is built on set theory—even if most practitioners never think about it that way. SQL operations like joins, unions, and intersections are direct implementations of set-based logic, enabling declarative data manipulation at scale. In an era of distributed query engines and vectorized execution, the principles of set theory are more relevant than ever—they’re just abstracted behind increasingly powerful engines.

These concepts might read like some dusty old tome found in some national archive but I think that they have shaped many of the incredible developments in the database world.

Gladstone Benjamin

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