Compliance in Databases: A Study of Structural Policies and Query Optimization

2026-04-17

AI Summary

This work addresses the complex interplay between content-sensitive access control policies and query optimization, which renders database performance difficult to predict. It introduces, for the first time, a structured policy syntax to formally model content-based compliance policies and systematically analyzes their impact on query planning and execution. Building on this formalism, the study develops a policy-aware query optimization framework and an extended benchmark suite, both integrated into a database execution engine. Experimental results demonstrate that policy structure significantly influences optimizer decisions and end-to-end performance, thereby establishing a theoretical foundation and empirical basis for the design of policy-aware database systems.

Technology Category

• Search and Optimization: Evaluation and Analysis
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Data Mining & Knowledge Management: Intelligent Query Processing

Application Category

• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs
• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

Abstract

Growing privacy regulations and internal governance mandates are driving demand for fine-grained, context-sensitive access control in data management systems. Among competing approaches, content-based access control -- where access decisions depend on the data values referenced by a query -- is becoming particularly prominent, and is supported directly in modern database engines. While simple content-based predicates often incur negligible overhead, increasingly rich policies can interact in subtle ways with query optimization, leading to significant and poorly understood performance variability. This paper investigates this gap by introducing a structural framework and expressive policy grammar for modelling content-based compliance policies and analysing their impact on query planning and execution in database systems. Building on this framework, we augment an analytical benchmark with structured policy workloads, enabling controlled evaluation of enforcement mechanisms and optimization strategies under combined query - policy workloads. Our experimental results show that policy structure has a decisive impact on optimizer behaviour and end-to-end performance, underscoring the need for policy-aware database and optimizer design.

Problem

• compliance
• content-based access control
• query optimization
• policy structure
• database performance

Innovation

• content-based access control
• policy-aware optimization
• structural policy framework
• query performance variability
• compliance enforcement