Archive for the Databases category
Ibrahim Sabek
September 21, 2026
Where Quantum Actually Meets the Database (and Where It Doesn’t)
Quantum computing might be the most famous technology that almost nobody has actually used. It shows up in movie plots, in nervous headlines about “the end of encryption,” and in the occasional promise that it will soon cure diseases, design new materials, and untangle city traffic, all at once. If you have heard exactly one […]
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Eugene Wu
July 4, 2025
Panel Summary: Where Does Academic Database Research Go From Here?
Date: Thursday, June 26, 2025 Organizers: Eugene Wu, Raul Castro Fernandez Panelists: Overview As organizers, we aimed to foster a bottom-up discussion on the evolving role and future direction of academic database research. Motivated by seismic technological and budgetary shifts, particularly the rise of AI, we explored the comparative advantage of the academic database community. This advantage is critical […]
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Eugene Wu
October 10, 2024
Where Does Database Research Go From Here?
The past few years of generative AI have upended research agendas across academia. Having just spent my sabbatical in the Bay Area, where the San Francisco fog is mixed with a tinge of forest fire and LLMs, I wanted to reflect on the role of the academic database research community within this sea change from the […]
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Kyle Deeds and Ziniu Wu
September 13, 2023
The Case for Cardinality Bounds: Principled Conservatism in Query Optimization
Introduction In the last decade, the database community has identified cardinality estimation as the primary stumbling block for modern query optimizers. Cardinality estimates, which estimate the size of sub-plan queries, are the primary basis for choosing between query plans, so poor estimates may result in catastrophic query execution plans. Research on this topic has consistently […]
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Mohamed Sharaf
February 16, 2023
Utilizing the Synergy between Query Refinement and View Recommendation for Visual Data Exploration
In this blog, we discuss the potential benefits of augmenting automated view recommendation solutions with query refinement techniques towards achieving insightful data exploration. Particularly, effective data exploration has been fueled by many approaches that rely on either view recommendation or query refinement, as two separate and independent techniques for gaining valuable insights from data. In […]
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