Speaker: Nesime Tatbul, Intel Science and Technology Center for Big Data based at MIT CSAIL
Title: S-Store: Streaming meets Transaction Processing
Managing high-speed data streams in real time has become an integral part of today’s big data applications. In a significant portion of these applications, we see a critical need for real-time stream processing to co-exist with transactional state management due to the presence of shared mutable state. Yet, existing systems treat streaming and transaction processing as two separate computational paradigms, which makes it difficult to build such applications to execute correctly and scalably. S-Store is a new data management system that provides a single, scalable platform for processing streams and transactions. S-Store takes its architectural foundation from H-Store - a modern distributed main-memory OLTP ("NewSQL") system, and adds well-defined primitives to support data-driven processing such as streams, windows, triggers, and dataflow graphs. Furthermore, it makes a number of careful extensions to H-Store's traditional transaction model in order to maintain correctness guarantees in the presence of data and processing dependencies among transaction executions that involve streams. These guarantees include ACID, ordered execution, and exactly-once processing. In this talk, I will present S-Store's design and implementation, and show how S-Store can ensure transactional integrity without sacrificing performance.
Nesime Tatbul is a senior research scientist at the Intel Science and Technology Center for Big Data based at MIT CSAIL. Before joining Intel Labs, she was a faculty member at the Computer Science Department of ETH Zurich. She received her B.S. and M.S. degrees in Computer Engineering from the Middle East Technical University (METU), and her M.S. and Ph.D. degrees in Computer Science from Brown University. During her graduate school years at Brown, she also worked as a research intern at the IBM Almaden Research Center, and as a consultant for the U.S. Army Research Institute of Environmental Medicine (USARIEM). Her research interests are in database systems, with a recent focus on data stream processing and distributed data management. She is the recipient of an IBM Faculty Award in 2008, a Best System Demonstration Award at the ACM SIGMOD 2005 Conference, and both the Best Poster Award and the Grand Challenge Award at the ACM DEBS 2011 Conference. She has served on the program committee for various conferences including ACM SIGMOD (as an industrial program co-chair in 2014 and as a group leader in 2011), VLDB, and IEEE ICDE (as a PC track chair for Streams, Sensor Networks, and Complex Event Processing in 2013). She has chaired a number of VLDB co-located workshops including the International Workshop on Data Management for Sensor Networks (DMSN) and the International Workshop on Business Intelligence for the Real-Time Enterprise (BIRTE). Her recent editorial duties include PVLDB (associate editor, Volume 5, 2011-2012) and ACM SIGMOD Record (associate editor, Research Surveys Column, since June 2012).