Scalable, Consistent, and Elastic Database Systems for Cloud Platforms


August 16, 2011


Sudipto Das


University of California


Cloud computing has emerged as a multi-billion dollar industry and as a successful paradigm for web application deployment. Economies-of-scale, elasticity, and pay-per-use pricing have been the biggest promises of cloud. Database management systems (DBMSs) serving these web applications form a critical component of the cloud software stack. These DBMSs must be able to scale-out to clusters of commodity servers to serve thousands of applications and their huge amounts of data. Moreover, to minimize the operating costs such DBMSs must also be elastic, i.e. posses the ability to increase and decrease the cluster size in a live system. This is in addition to serving a variety of applications (i.e. support multitenancy) while being self-managing, fault-tolerant, and highly available.

The overarching goal of my research is to propose abstractions, protocols, and paradigms to design efficient and scalable database management systems that address the unique set of challenges posed by the cloud. My dissertation shows that with careful choice of design and features, it is possible to architect scalable DBMSs that efficiently execute transactions at scale to ease application design while being elastic and self-managing to simplify deployment and management. In this talk, I will outline my work that embodies this principle. In the first part, I will present techniques and system architectures to enable efficient and scalable transaction processing on clusters of commodity servers. In the second part, I will present techniques for on-demand database migration in a live system, a primitive operation critical to support lightweight elasticity as a first class notion in DBMSs. I will conclude the talk with a discussion of possible future directions.


Sudipto Das

Sudipto Das is a PhD candidate in the Department of Computer Science at University of California, Santa Barbara (UCSB) advised by Professors Divy Agrawal and Amr El Abbadi. He received his B. Engg. degree (honors) in Computer Science and Engineering from Jadavpur University (JU), India in 2006. His research interests lie in the area of designing scalable data management infrastructures spanning both transaction processing and data analysis systems. His works have been published in prestigious and highly selective venues showcasing database research, such as SIGMOD, VLDB, ICDE, CIDR, MDM, and SoCC. He is the recipient of the CIDR 2011 Best Paper Award, MDM 2011 Best Runner-up Paper Award, 2011 Outstanding Student Award in CS at UCSB, and the TCS-JU Best Student Award for 2006. For more information, visit: