Conflict-robustness implies view-robustness in multiversion concurrency control.
Proposing new decidable criteria for ensuring finite chase termination in tuple-generating dependencies.
Hydro utilizes adaptive query processing to efficiently process ML queries by dynamically adjusting the query plan during execution.
A novel graph-based approach quantifies semantic dissimilarity between SQL queries, providing accurate grading and meaningful feedback.
WaZI is a learned and workload-aware variant of the Z-index, optimizing storage layout and search structures for spatial query performance.
Innovative runtime optimization techniques using Adaptive Metaprogramming significantly improve the performance of recursive queries.
Processing-in-Memory technology accelerates path matching in graph databases, overcoming memory wall bottlenecks.
Learned indexes in multi-dimensional spaces aim to improve search performance and reduce space requirements by leveraging Machine Learning models to map keys to positions within datasets.