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…
The Case for Cardinality Lower Bounds
Mihail Stoian, Tiemo Bang, Hangdong Zhao +3
Despite decades of research, cardinality estimation remains the optimizer's Achilles heel, with industrial-strength systems exhibiting a systemic tendency toward underestimation. A…
GRACEFUL: A Learned Cost Estimator For UDFs
Johannes Wehrstein, Tiemo Bang, Roman Heinrich +1
User-Defined-Functions (UDFs) are a pivotal feature in modern DBMS, enabling the extension of native DBMS functionality with custom logic. However, the integration of UDFs into que…
SkyStore: Cost-Optimized Object Storage Across Regions and Clouds
Shu Liu, Xiangxi Mo, Moshik Hershcovitch +11
Modern applications span multiple clouds to reduce costs, avoid vendor lock-in, and leverage low-availability resources in another cloud. However, standard object stores operate wi…
Optimizing the cloud? Don't train models. Build oracles!
Tiemo Bang, Conor Power, Siavash Ameli +2
We propose cloud oracles, an alternative to machine learning for online optimization of cloud configurations. Our cloud oracle approach guarantees complete accuracy and explainabil…
AnyDB: An Architecture-less DBMS for Any Workload
Tiemo Bang, Norman May, Ilia Petrov +1
In this paper, we propose a radical new approach for scale-out distributed DBMSs. Instead of hard-baking an architectural model, such as a shared-nothing architecture, into the dis…