Tag Archives: H-Store

Rethinking Streaming: Correct State Matters!

by Nesime Tatbul, Intel Labs and MIT CSAIL; Kristin Tufte, Portland State University; and Stan Zdonik, Brown University Stream processing has largely been thought of as real-time analytics. Data enters the system as streams and analytic functions (aggregates) are computed on the … Continue reading

Posted in Big Data Applications, DBMS, ISTC for Big Data Blog, Streaming Big Data | Tagged , , , , , , , , , | Leave a comment

Larger-than-Memory Data Management on Modern Storage Hardware for In-Memory OLTP Database Systems

By Lin Ma, Carnegie Mellon University; Joy Arulraj, Carnegie Mellon University; Sam Zhao, Brown University; Andrew Pavlo, Carnegie Mellon University; Subramanya R. Dulloor, Intel Labs; Michael J. Giardino, Georgia Institute of Technology; Jeff Parkhurst, Jason L. Gardner, Kshitij Doshi, Intel Labs; and Col. Stanley Zdonik, Brown … Continue reading

Posted in Big Data Architecture, Data Management, DBMS, ISTC for Big Data Blog, Storage | Tagged , , , , , | Leave a comment

S-Store: A Big-Velocity Database System

By John Meehan, PhD Candidate, Brown University At the 2014 Intel Science and Technology Center for Big Data annual Research Retreat, Nesime Tatbul of Intel Labs and MIT provided an update on S-Store. Background Recently, the architectures of transactional processing DBMSs … Continue reading

Posted in Analytics, Big Data Applications, ISTC for Big Data Blog, Streaming Big Data | Tagged , , , , , , | Leave a comment

OLTP Database Systems for Non-Volatile Memory

By Joy Arulraj, Justin Debrabant, Andrew Pavlo, Michael Stonebraker, Stan Zdonik, and Subramanya Dulloor In this joint collaboration between Brown, CMU, MIT CSAIL and Intel Labs, we explore two possible use cases of Non-Volatile Memory (NVM) for on-line transaction processing (OLTP) DBMSs. Evaluation of software systems using NVM is challenging … Continue reading

Posted in Big Data Architecture, Computer Architecture, DBMS, ISTC for Big Data Blog | Tagged , , , , , | Leave a comment

S-Store: Real-Time Analytics Meets Transaction Processing

By Nesime Tatbul, Intel Labs and MIT Managing high-speed data streams generated in real time is an integral part of today’s big data applications. In a wide range of domains from social media to financial trading, there is a growing … Continue reading

Posted in Big Data Applications, Databases and Analytics, DBMS, ISTC for Big Data Blog, Streaming Big Data | Tagged , , , , , | Leave a comment

Concurrency Control in the Many-core Era: Scalability and Limitations

By Xiangyao Yu, George Bezerra, Michael Stonebraker and Srini Devadas of MIT CSAIL and Andrew Pavlo of Carnegie Mellon University Computers are moving towards an era dominated by many-core machines with dozens or even hundreds of cores on a single chip. This unprecedented … Continue reading

Posted in Big Data Architecture, Computer Architecture, DBMS, ISTC for Big Data Blog | Tagged , , , , | Leave a comment

Reflections on the First Year of the ISTC for Big Data

By Sam Madden, MIT CSAIL A year ago, Intel announced that our team had been selected to host the Intel Science and Technology Center in Big Data.  This seemed like a good opportunity to reflect on some of the awesome … Continue reading

Posted in Analytics, Big Data Architecture, Databases and Analytics, DBMS, ISTC for Big Data Blog, Tools for Big Data, Visualizing Big Data | Tagged , , , , , , , , , , , | Leave a comment

Anti-Caching and Non-Volatile Memory for Transactional DBMS

By Andy Pavlo of Brown University and Mike Stonebraker of MIT CSAIL The traditional wisdom for building disk-based database management systems (DBMSs) is to organize blocks of data on disk, with a main memory block cache. In order to improve performance given high disk … Continue reading

Posted in Big Data Architecture, Computer Architecture, DBMS, ISTC for Big Data Blog | Tagged , , | Leave a comment