ACM SIGMOD City, Country, Year
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Edgar F. Codd Innovations Award

Presented to Raghu Ramakrishnan for his pioneering work in deductive databases and their application to relational databases in practice.


Raghu Ramakrishnan is CTO for Data, and a Technical Fellow at Microsoft. He has previously served as Chief Scientist at Yahoo! and Professor at the University of Wisconsin-Madison, in addition to being founder and CTO of QUIQ, an early online crowd-sourced question-answering company. He graduated from IIT Madras and received his PhD from the University of Texas at Austin. At Wisconsin, he wrote the text ''Database Management Systems'' and led the development of the widelydistributed CORAL deductive database, as well as projects on data mining, information integration, image databases, and querying ordered data. This early work influenced commercial query optimizers as well as the design of window functions in SQL:1999, and has received the SIGMOD Test-of-Time Award for a paper on clustering and the ICDT Test-of-Time Award for a paper on nearest-neighbor indexing. At Yahoo!, he led the research for major initiatives, including the CORE project that was the foundation for Yahoo's personalized portal pages, the PNUTS geo-replicated cloud service deployed in 18+ regions world-wide, and Yahoo!'s web-scale information extraction for semantic results in Yahoo! Search. At Microsoft, he founded the CISL applied research team and led the development of Azure Data Lake, Microsoft's exabyte-scale storage and analytics platform, with research contributions to scale-out tiered storage and resource management in YARN. Ramakrishnan has received the ACM SIGKDD Innovations Award, the ACM SIGMOD Contributions Award, a Distinguished Alumnus Award from IIT Madras, a Packard Foundation Fellowship and the NSF Presidential Young Investigator Award. He is a Fellow of the ACM and IEEE. He has served on the boards of ACM SIGKDD, the VLDB Foundation, and ACM SOCC, and is a past chair of ACM SIGMOD.

SIGMOD Contributions Award

Presented to Z. Meral Özsoyoğlu for dedicated service to the database community, especially as editor in chief for ACM TODS and PVLDB, the VLDB Endowment and acting as PC chair for VLDB PC and PODS.


Zehra Meral Özsoyoğlu is currently Andrew R. Jennings Professor Emeritus of Computer Science at Case Western Reserve University, in Cleveland, Ohio, where she has been a professor of Computer Science since 1980. She has also served as department chair of Electrical Engineering and Computer Science Department. Meral Özsoyoğlu's primary work and research interests are in the areas of query languages and query processing, data models, and index structures in databases, including scientific databases, bioinformatics and medical informatics. More recently, she has been working in querying databases with graph query templates. Meral Özsoyoğlu has served in a variety of leadership roles in the computer science research community, more specifically in database research, including the program chair of international conferences VLDB 2012, IEEE ICDE 2004, ACM PODS 1997 and SSDBM 1999. She also served in many conference program committees. She has been the Editor-in-Chief of ACM Transactions of Database Systems 2007-2014, and the Editor-in-Chief of PVLDB, Vol. 5, 2011-2012. She has been a trustee of the VLDB Endowment 2005- 2011, an Associate Editor of ACM TODS, 2000-2007, Vice Chair of ACM SIGMOD, 1997-2001, Associate Editor of IEEE TKDE journal, 1999-2002, and Editor of IEEE Data Engineering Bulletin. She is an ACM Fellow, recipient of the IBM Faculty Award, NSF Faculty Award for Women, a Distinguished Alumni Award from University of Alberta, Spotlight on Women Scholarship in Engineering award, and Faculty Distinguished Research Award, Case Western Reserve University (2013) and awards from IEEE and ACM for contributions to program committees of conferences. She received her BSc in Electrical Engineering, and MSc in Computer Science from the Middle East Technical University, Ankara, Turkey and PhD in Computer Science from the University of Alberta, Edmonton, Canada.

SIGMOD Test-of-Time Award

Serializable isolation for snapshot databases

Michael Cahill (MongoDB), Uwe Roehm (University of Sydney, Australia), Alan Fekete (University of Sydney, Australia)

Many popular database management systems implement a multiversion concurrency control algorithm called snapshot isolation rather than providing full serializability based on locking. There are well-known anomalies permitted by snapshot isolation that can lead to violations of data consistency by interleaving transactions that would maintain consistency if run serially. Until now, the only way to prevent these anomalies was to modify the applications by introducing explicit locking or artificial update conflicts, following careful analysis of conflicts between all pairs of transactions.This article describes a modification to the concurrency control algorithm of a database management system that automatically detects and prevents snapshot isolation anomalies at runtime for arbitrary applications, thus providing serializable isolation. The new algorithm preserves the properties that make snapshot isolation attractive, including that readers do not block writers and vice versa. An implementation of the algorithm in a relational DBMS is described, along with a benchmark and performance study, showing that the throughput approaches that of snapshot isolation in most cases.


Dr. Michael Cahill is the VP Engineering (Storage) at MongoDB. He was a founder and architect at WiredTiger before its acquisition by MongoDB. Prior to that, he was an architect of Berkeley DB at Sleepycat Software and Oracle Corp., responsible for design and implementation of multiversion concurrency control, as well as SQL interfaces and programming language APIs. Previously, Dr. Cahill was CTO at Bullant Technology, which grew tenfold and raised over US$30 million from investors including Intel Capital and JP Morgan during his three year tenure. Dr. Cahill's PhD from the University of Sydney is in the area of transaction processing and concurrency control. His work on a new algorithm for implementing serializable isolation received an ACM SIGMOD Best Paper award in 2008 and was added to PostgreSQL 9.1.

Uwe Roehm is Associate Professor in Database Systems at the University of Sydney. He is a computer science graduate from the University of Passau, Germany, and completed his PhD at ETH Zurich under Professor Hans-Joerg Schek in the area of combining OLTP/OLAP workloads in a cluster of databases. Much of his research has dealt with transaction management and replication, especially how to ensure sufficient freshness in values read. He has also worked on optimising database systems for multi-core servers. Another agenda in Uwe's research is in-database support of bioinformatics and other biomedically-important computations. He has been a visiting researcher at Microsoft, and held visiting positions at the University of Queensland, at the Karlsruhe Institute of Technology (KIT), and at TU Munich.

Alan Fekete is Professor of Enterprise Software Systems at the University of Sydney in Australia. He completed a BSc from University of Sydney, then a PhD from Harvard University, and he has held visiting positions at Cornell, MIT, U Washington, Microsoft Research, and UC Berkeley. Alan has an extensive history of work on the topic of transaction management. His research focus is currently on how to help application programmers understand and exploit the properties and performance of data management services that offer lower support for consistency or isolation. He also has published on theory of distributed computing (especially consensus techniques), formal methods for software engineering, and computing education. Alan has been recognized as ACM Distinguished Scientist.

SIGMOD Jim Gray Doctoral Dissertation Award

ACM SIGMOD is pleased to present the 2018 SIGMOD Jim Gray Doctoral Dissertation Award to Viktor Leis. Viktor completed his dissertation titled "Query Processing and Optimization in Modern Database Systems" at the Technical University of Munich under the supervision of Thomas Neumann and Alfons Kemper.


Viktor Leis is a postdoctoral researcher at the Technical University of Munich, where he received a doctorate in Computer Science in 2016, advised by Thomas Neumann and Alfons Kemper. Much of his research, which includes work on query processing, query optimization, concurrency control, index structures, and storage, has been integrated into the HyPer database system, which was acquired by Tableau in 2016. He received the biennial dissertation award of the German-speaking database community (GI DBIS) and best paper awards at ICDE 2014 and ICDE 2018.

SIGMOD Jim Gray Doctoral Dissertation Award (Honorable Mention)

ACM SIGMOD is pleased to recognize Luis Galárraga with an Honorable Mention for the 2018 SIGMOD Jim Gray Doctoral Dissertation Award. Luis completed his dissertation titled ''Rule Mining in Knowledge Bases'' at Telecom ParisTech under the supervision of Fabian Suchanek.

Luis Galárraga is an Inria researcher working at the IRISA research center in Rennes. In 2008 he obtained his bachelor's degree in Computer Engineering at ESPOL (Escuela Superior Politenica del Litoral) in Ecuador. Then he pursued a master in computer science at Saarland University in Germany. In 2012 he was granted an IMPRS scholarship to pursue his PhD studies and joined the Ontologies Group, leaded by Fabian Suchanek, at the Max Planck Institute for Informatics in Saarbrucken. The group eventually moved to Telecom ParisTech in France, where Luis obtained his doctoral degree in September 2016 for his work on rule mining on knowledge bases. Right after, he joined the Computer Science Department of Aalborg University as a postdoctoral researcher where he worked with Katja Hose. Luis' research work and interests fall within the domains of semantic web, SPARQL query optimization, knowledge management, and data mining. He is currently part of the team LACODAM specialized in pattern mining at IRISA.

SIGMOD Jim Gray Doctoral Dissertation Award (Honorable Mention)

ACM SIGMOD is also pleased to recognize Yongjoo Park with an Honorable Mention for the 2018 SIGMOD Jim Gray Doctoral Dissertation Award. Yongjoo completed his dissertation titled "Fast Data Analytics by Learning" at the University of Michigan under the supervision of Michael Cafarella and Barzan Mozafari.

Yongjoo Park is a Research Fellow in Computer Science and Engineering at the University of Michigan, Ann Arbor. His research interests are developing algorithms and building systems for large-scale data analytics. His Ph.D. study mainly focused on building fast Approximate Query Processing systems by applying machine learning. He received a Ph.D. from the University of Michigan, Ann Arbor, advised by Michael Cafarella and Barzan Mozafari. He received a B.S. from Seoul National University. He is a recipient of Jeongsong Graduate Study Fellowship and Kwanjeong Ph.D. Fellowship.

SIGMOD Best Paper Award

SuRF: Practical Range Query Filtering with Fast Succinct Tries


Huanchen Zhang (Carnegie Mellon University), Hyeontaek Lim (Carnegie Mellon University), Viktor Leis (TUM), David Andersen (Carnegie Mellon University), Michael Kaminsky (Intel Labs), Kimberly Keeton (Hewlett Packard Labs), Andrew Pavlo (Carnegie Mellon University)

Huanchen Zhang is a fifth-year Ph.D. student in the Computer Science Department at Carnegie Mellon University. He received his B.S. degrees in Computer Engineering, Computer Sciences, and Mathematics from University of Wisconsin-Madison. His research interests center on database and storage systems. He has a particular interest in building space-efficient and high-performance in-memory search structures.

Hyeontaek Lim is a Post Doctoral Fellow in the Computer Science Department at Carnegie Mellon University. He received a Ph.D. in Computer Science from Carnegie Mellon University and received a B.S. in Computer Science from KAIST.

Viktor Leis is a postdoctoral researcher at the Technical University of Munich, where he received a doctorate in Computer Science in 2016, advised by Thomas Neumann and Alfons Kemper. Much of his research, which includes work on query processing, query optimization, concurrency control, index structures, and storage, has been integrated into the HyPer database system, which was acquired by Tableau in 2016. He received the biennial dissertation award of the German-speaking database community (GI DBIS) and best paper awards at ICDE 2014 and ICDE 2018.

David Andersen is an associate professor in the Computer Science department at Carnegie Mellon University. He received his Ph.D. and M.S. degrees from MIT, and received B.S. degrees in Computer Science and Biology from the University of Utah. Before joining MIT, he was a co-founder and CTO of an Internet Service Provider in Salt Lake City. His research interests center on computer systems in the networked environment.

Michael Kaminsky is a senior research scientist in Intel Labs and an adjunct faculty member of the Computer Science Department at Carnegie Mellon University. He is currently part of the Intel Science and Technology Center for Visual Cloud Systems (ISTC-VCS), based in Pittsburgh, PA at Carnegie Mellon. Michael joined Intel in Summer 2004 after completing his Ph.D. in Computer Science at MIT. His research interests include distributed systems, operating systems, and networking.

Dr. Kimberly Keeton is a Distinguished Technologist at Hewlett Packard Labs. She earned her Ph.D. and M.S. in Computer Science from the University of California at Berkeley and her B.S. in Computer Engineering and Engineering and Public Policy from Carnegie Mellon. Her recent research is in the areas of NVM-aware data stores and data analytics frameworks in the context of The Machine project at HPE. She has also worked in the areas of storage and information management, NoSQL databases, storage dependability, intelligent storage, and workload characterization. She was a co-architect of the Express Query database, which provides metadata services for HPE's StoreAll file archiving solution. She is an ACM Distinguished Scientist and a Senior Member of the IEEE, and has served as Technical Program Committee Chair for USENIX OSDI, ACM EuroSys, ACM SIGMETRICS, USENIX FAST and IEEE/IFIP DSN/Performance and Dependability Symposium.

Andy Pavlo is an Assistant Professor of Databaseology in the Computer Science Department at Carnegie Mellon University. He also used to raise clams.

SIGMOD Software Systems Award: The Hive and PIG Database Systems

For developing seminal software systems that served to bring relational-style declarative programming to the Hadoop ecosystem.


Jeff Hammerbacher (MUSC), Ashish Thusoo (Qubole), Joydeep Sen Sarma (Qubole)


Jeff Hammerbacher is an Assistant Professor at MUSC, an investor at Techammer, and a board member at Ciox and Cytel. Previously, Jeff was an Assistant Professor at Mount Sinai, a founder and Chief Scientist of Cloudera, an Entrepreneur in Residence at Accel Partners, manager of the Data team at Facebook, and a fixed income quant at Bear Stearns. He earned his Bachelor's Degree in Mathematics from Harvard University.

Ashish Thusoo is the CEO and co-founder of Qubole, a cloud-native big data activation platform that selfmanages, self-optimizes, and learns to improve automatically in order to vastly simplify the operationalization of enterprise data lakes using the cloud. Before co-founding Qubole, Ashish ran Facebook's Data Infrastructure team; under his leadership the team built one of the largest data processing and analytics platforms in the world. At Facebook Ashish co-created Apache Hive and brought SQL capabilities to the new age data processing architectures and in the process helped to create the big data industry.

Joydeep Sen Sarma is CTO and co-founder at Qubole - one of the largest providers of Big-Data-as-aService - where he leads technology initiatives with a particular focus on building cloud-native data processing technologies and autonomous computing. Joydeep was an early engineer at Facebook where he brought up their Hadoop based data infrastructure, started what became Apache Hive, managed the Data Infrastructure team, and was a key architect on FB Messages. Joydeep graduated from IIT-Delhi and the University of Pittsburgh and worked on databases, file systems, high availability, and behavioral targeting and recommender systems at Oracle, Netapp and Yahoo.


Christopher Olston (Google), Benjamin Reed (Facebook), Utkarsh Srivastava (Google)


Christopher Olston is a staff research scientist at Google, specializing in machine-learning infrastructure. His past research focused on large-scale data management and web data techniques (e.g. crawling). He delivered a keynote talk at the 2011 ACM Symposium on Cloud Computing, and won the 2009 ACM SIGMOD Best Paper Award. Olston holds computer science degrees from Stanford (Ph.D., M.S.) and UC Berkeley (B.S.).

Benjamin Reed is working in the area of mobile computing and core infrastructure systems at Facebook to help make the world more open and connected. Before joining Facebook, Benjamin worked on Pig at Yahoo! Research. He received a PhD in computer science from the University of California, Santa Cruz in 2000. In the fall of 2018 he will join the faculty of the San Jose State University Department of Computer Science to teach and research distributed systems and data management.

Utkarsh Srivastava has held engineering leadership positions at Google and Twitter where he has helped to build large-scale systems for content serving and ranking. Prior to that, Utkarsh helped to build Yahoo's first multi-data-center distributed database, and Pig, a high-level query language over Hadoop. Utkarsh holds a PhD from Stanford and a bachelors from IIT Kanpur.

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