Tailwind introduces ALPs and ML-based planning to integrate workload-specific query accelerators into standard RDBMSes, achieving 1.38x average (up to 29x) speedup on TPC-H queries.
Mior, and Daniel Lemire
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
method 1polarities
use method 1representative citing papers
Proposes Governed Evolving Memory (GEM) as a state-trajectory workload for long-term AI agent memory using four operators and six correctness conditions that record-level systems cannot satisfy.
citing papers explorer
-
Tailwind: A Practical Framework for Query Accelerators
Tailwind introduces ALPs and ML-based planning to integrate workload-specific query accelerators into standard RDBMSes, achieving 1.38x average (up to 29x) speedup on TPC-H queries.
-
Is Agent Memory a Database? Rethinking Data Foundations for Long-Term AI Agent Memory
Proposes Governed Evolving Memory (GEM) as a state-trajectory workload for long-term AI agent memory using four operators and six correctness conditions that record-level systems cannot satisfy.