Tianyu will present this paper in this meeting: Title: Faster: A Concurrent Key-Value Store with In-Place Updates Authors: Badrish Chandramouli , Guna Prasaad , Donald Kossmann , Justin Levandoski , James Hunter , Mike Barnett Read More

Lin will present this work in this meeting: Title: Automatically Indexing Millions of Databases in Microsoft Azure SQL Database Authors: Sudipto Das, Miroslav Grbic, Igor Ilic, Isidora Jovandic, Andrija Jovanovic, Vivek R. Narasayya, Miodrag Radulovic, Maja Stikic, Gaoxiang Xu, Surajit Chaudhuri Read More

Prashanth will present the following paper in this meeting: Title: Thriving in the No Man’s Land between Compilers and Databases Authors: Holger Pirk, Jana Giceva, Peter Pietzuch Read More

Dana will present the following paper in this meeting: Title: Automated Performance Management for the Big Data Stack Authors: Anastasios Arvanitis, Shivnath Babu, Eric Chu, Adrian Popescu, Alkis Simitsis, Kevin Wilkinson Read More

Project 1: Storage Engine (Tianyu Li & Matt Butrovich) In this talk, we will discuss the work we've done on terrier's storage engine over the semester. We will cover the implementation of write-ahead logging and our proposed model for recovery, implementation of indexes, and our roadmap for the storage engine next semester. The immediate future direction for the storage work... Read More

Following from the idea that "one size no longer fits for all", a family of "NewSQL" specialized databases arose. To handle OLTP, researchers at MIT and Brown (and a few other places) built H-Store, a distributed, shared-nothing, in-memory database that got rid of locking, latching, buffering, and logging, beating the performance of traditional OLTP RDBMSs by nearly two orders of... Read More

n the last two decades, both researchers and vendors have built advisory tools to assist database administrators (DBAs) in various aspects of system tuning and physical design. Most of this previous work, however, is incomplete because they still require humans to make the final decisions about any changes to the database and are reactionary measures that fix problems after they... Read More

Online Analytical Processing (OLAP) of very large data sets and/or high-velocity data is a workload that strains all parts of a compute system: storage bandwidth, IO-subsystem throughput, main-memory bandwidth, instruction-level concurrency and thread-parallelism. Swarm64 seeks to improve the effective throughput and the compute efficiency of OLAP workloads by adding FPGAs as additional compute element to standard compute servers. The hard-... Read More

Modern query-heavy applications of database systems especially require minimal delays to OLAP queries, as well as allowing the lasted OLTP updates to be visible in time. A popular mechanism for fast response to OLAP queries is to use snapshot isolation (SI) for multi-version concurrency control (MVCC), as it allows readers to make progress regardless of concurrent writers. Many other optimizations... Read More

In this talk, we will cover how the implementation of GPU database management systems are different than CPU database systems and provide evidence that shows how much of the performance gains with these systems are achieved via just GPUs. We will also discuss how we are solving the problems of tomorrow – making AI smarter, faster and more intuitive with... Read More