Computation-proximate architecture: an actor-based pattern for real-time calculations over billion-row datasets
Abstract
Abstract Organizations processing historical datasets with billions of rows face a fundamental architectural choice: move data to computation (the traditional query-centric approach) or move computation to data. This paper presents the \textbf{Computation-Proximate Pattern}, an architecture that combines actor-based in-memory computation with tiered caching and row-key value stores to achieve sub-15ms response times over billion-row datasets. The pattern eliminates unnecessary data movement by resolving 70\% of data lookups from a two-level cache hierarchy---50\% from in-process L1 caches ($
Fields of Study & Subjects
Advanced Database Systems and Queries
Cloud Computing and Resource Management
Parallel Computing and Optimization Techniques
Publication details
- Journal / source
- Distributed and Parallel Databases
- Volume
- 44
- Issue
- 1
- Publication date
- 27 August 2026
- Language
- EN