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Design Tradeoffs of Data Access Methods, at Tutorial at SIGMOD 2016
tutorialsigmod16part1.pdf
tutorialsigmod16part2.pdf

Database researchers and practitioners have been building methods to store, access, and update data for more than five decades. Designing access methods has been a constant effort to adapt to the ever changing underlying hardware and workload requirements. The recent explosion in data system designs – including, in addition to traditional SQL systems, NoSQL, NewSQL, and other relational and non-relational systems – makes understanding the tradeoffs of designing access methods more important than ever. Access methods are at the core of any new data system. In this tutorial we survey recent...

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Database Architectures for Big Data Exploration, at Keynote in French Database Conference, October, 2013
keynotebda.pdf

We are now entering the era of data deluge, where the amount of data outgrows the capabilities of query processing technology. Many emerging applications, from social networks to scientific experiments, are representative examples of this deluge, where the rate at which data is produced exceeds any past experience. For example, scientific analysis such as astronomy is soon expected to collect multiple Terabytes of data on a daily basis, while already web-based businesses such as social networks or web log analysis are confronted with a growing stream of large data inputs. State-of-...

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Database Cracking and the Path Towards Auto-tuning Database Kernels, at Faculty Job Talk, Spring 2013
crackingbigdata.pdf

Today, businesses and sciences create more data than what we can store, move, let alone analyze. A fundamental problem with big data is that data management systems require extensive tuning (indexing) and installation steps; by the time we finish tuning, more data have already arrived. To make things worse, tuning a database system requires knowledge of what to tune for, i.e., we need to know the kind of queries we will be posing. However, in several modern big data applications, we are often in need of exploring new data quickly, searching for interesting patterns without knowing a...

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