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Monotonicity in Databases and APIs

2 posts · Sep 2022 – Sep 2025

What this trail covers

This post details the evolution of Palantir's approach to designing systems with monotonicity in mind, extending previous discussions on databases and APIs. It emphasizes how understanding and leveraging monotonicity can lead to more efficient query optimization, robust API design, and stronger system invariants. The post likely elaborates on practical implementation strategies and trade-offs, particularly in scenarios involving data deletion or complex state management, building upon the foundational concepts of monotonic queries and APIs.

All Palantir trails
  1. MediumThis post extends the discussion on monotonicity by detailing its practical implications for query optimization in relational databases and API design. It elaborates on how monotonic APIs can prevent race conditions and ensure data integrity in service-oriented architectures. The post also addresses the trade-offs between monotonicity and deletion requirements, offering insights into managing these complexities in real-world systems.
  2. On Monotonicity in Relational Databases and Service-oriented ArchitectureThis post introduces the concept of monotonicity in relational databases and REST APIs. For databases, it explains how monotonic queries (where adding data never removes results) simplify optimization and analysis, contrasting them with non-monotonic queries involving negation. For REST APIs, it defines API monotonicity as the inability to remove information through API interactions and demonstrates how this property can be used to enforce cross-service invariants, such as ensuring every account has a valid policy. It also discusses the challenges of supporting deletion while maintaining monotonicity and adhering to data minimization principles.