12 citations · 18 across the 4 of their papers we have counts for
6 papers
Towards an AI Software Factory for Data Systems
Anna Pavlenko, Bogdan Crivat, Brandon Haynes +23
AI-assisted coding tools deliver significant acceleration of coding, but only limited impact across the end-to-end software development lifecycle (SDLC)--an Amdahl's law effect! In…
AutoComp: Automated Data Compaction for Log-Structured Tables in Data Lakes
Anja Gruenheid, Jesús Camacho-Rodríguez, Carlo Curino +7
The proliferation of small files in data lakes poses significant challenges, including degraded query performance, increased storage costs, and scalability bottlenecks in distribut…
Optimizing open-domain question answering with graph-based retrieval augmented generation
Joyce Cahoon, Prerna Singh, Nick Litombe +6
In this work, we benchmark various graph-based retrieval-augmented generation (RAG) systems across a broad spectrum of query types, including OLTP-style (fact-based) and OLAP-style…
Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse Ecosystem: Can One QO Rule Them All?
Rana Alotaibi, Yuanyuan Tian, Stefan Grafberger +13
Customer demand, regulatory pressure, and engineering efficiency are the driving forces behind the industry-wide trend of moving from siloed engines and services that are optimized…
Sibyl: Forecasting Time-Evolving Query Workloads
Hanxian Huang, Tarique Siddiqui, Rana Alotaibi +6
Database systems often rely on historical query traces to perform workload-based performance tuning. However, real production workloads are time-evolving, making historical queries…
MotherNet: Fast Training and Inference via Hyper-Network Transformers
Andreas Müller, Carlo Curino, Raghu Ramakrishnan
Foundation models are transforming machine learning across many modalities, with in-context learning replacing classical model training. Recent work on tabular data hints at a simi…