Tag Archives: H-Store

The Big Data ISTC: A Retrospection by Michael Stonebraker, Samuel Madden and Timothy Mattson

The Big Data ISTC is a research project sponsored by Intel that ran for five years (August 2012- August 2017).  This blog post highlights some of the accomplishments and lessons learned during this period. Big data is usually categorized into … Continue reading

Posted in Analytics, Benchmarks, Big Data Applications, Big Data Architecture, Data Management, Databases and Analytics, DBMS, ISTC for Big Data Blog, Polystores, Query Engines, Storage, Streaming Big Data, Tools for Big Data, Visualizing Big Data | Tagged , , , , , , , , , , , , , , , , , , , , , , | Leave a comment

ISTC Releases Open Source Code for S-Store Transactional Streaming System

By John Meehan and Stan Zdonik, Brown University & Nesime Tatbul, Intel Labs and MIT Today, the ISTC for Big Data released the first version of our S-Store transactional stream processing system. S-Store is open-source software and available for download … Continue reading

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

Intel and the ISTC for Big Data (2012-2017): A Powerful Collaboration

By Jeff Parkhurst, Ph.D. and Timothy G. Mattson, Ph.D., Intel  The year 2012 was arguably the year that Big Data went mainstream. Data was being hailed as a new class of economic asset, similar to currency or gold, from the … Continue reading

Posted in Benchmarks, Big Data Architecture, Data Management, Databases and Analytics, ISTC for Big Data Blog, Polystores, Streaming Big Data, Tools for Big Data, Visualizing Big Data | Tagged , , , , , , , , | Leave a comment

Solving the “One Concurrency Control Does Not Fit All” Problem for OLTP Databases

By Dixin Tang and Aaron J. Elmore, University of Chicago In this post, we present a new transactional database system that adaptively changes data organization and concurrency control protocols in response to workload changes. With the increasing memory sizes of … Continue reading

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

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