Relational Thinking Beyond SQL Assumptions at WWDVC 2026

This article examines a workshop presented at the Worldwide Data Vault Consortium 2026 that addresses the persistent gap between everyday SQL usage and the foundational relational model. The session focuses on exposing why reliance on SQL syntax alone does not guarantee relational correctness, especially when dealing with nulls, unknowns, and three-valued logic that introduce ambiguity undermining trust and auditability.

Clarifying the True Relational Model

The workshop begins by defining what it means for a database management system to be genuinely relational, a concept often obscured by SQL’s deviations from relational principles. This distinction is critical because many systems labeled relational do not fully embody the relational model’s rigor, impacting how data is structured and interpreted. Understanding this difference affects the design of business key structures and association relationships, which underpin long-term data clarity and reuse.

Returning to relational fundamentals reveals why databases must adhere to these principles to maintain consistency and correctness at scale. This clarity is essential for architects and modelers who must reconcile the theoretical model with the practical realities of SQL-based implementations, where implicit assumptions can lead to silent failures in data logic and interpretation.

Nullology and the Challenge of Empty Sets

Nullology, the study of empty sets within relational contexts, highlights a subtle but pervasive issue in data modeling and querying. The workshop explores scenarios where relations contain no tuples, a condition that resembles empty files but carries nuanced implications for data integrity and logic. Recognizing how empty sets manifest and influence relational operations is crucial for maintaining audit trails and ensuring that missing information does not propagate unnoticed through analytic pipelines.

Views, Virtualization, and Updating Complexity

Views serve as virtual tables, and their updatability is not merely a convenience but a necessity for maintaining data integrity across layers of abstraction. The session challenges the long-held skepticism about view updating by presenting a theory consistent with relational principles that supports updating views as reliably as base tables. This has direct implications for the use of virtualization in analytic marts and temporal descriptive data structures, where updates must preserve correctness without introducing ambiguity.

Understanding how updates propagate through views affects control objectives related to data consistency and reconciliation routines. It also influences the operating model boundaries between physical data stores and their virtual representations, which are often sources of confusion and error in enterprise environments.

Moreover, the workshop addresses the limitations of current SQL implementations in this regard, underscoring the gap between theoretical rigor and practical tooling.

Nulls, Three-Valued Logic, and the Closed World Assumption

The relational model is founded on two-valued logic, but SQL introduces three-valued logic to handle missing information through nulls, a design choice that the workshop critiques thoroughly. This approach fails to solve the problem it aims to address and can introduce dangerous ambiguities that erode trust in data outputs. Recognizing these limitations is vital for architects who design systems requiring defensible analytics and clear auditability.

The session further explains the Closed World Assumption (CWA), which posits that all information in the database is true and anything not stated is false. This assumption contrasts with the Open World Assumption and provides a more reliable foundation for handling missing data without resorting to nulls or three-valued logic. Implementing CWA-based designs supports stronger accountability through explicit decision rights about data completeness and correctness.