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Joy Arulraj
Associate Professor Georgia Institute of Technology College of Computing School of Computer Science arulraj@gatech.edu Klaus Advanced Computing Building 3324 266 Ferst Dr NW, Atlanta, GA 30332-0765 CV | Google Scholar | DBLP | Twitter | Github Research Groups Data Systems and Analytics Group Research Interests Data Systems, Machine Learning We are developing the EVA AI-Relational Data System. I am
TPCC_Node_Standard.eps
Lightweight Locking for Main Memory Database Systems Kun Ren†* kun@cs.yale.edu Alexander Thomson* thomson@cs.yale.edu Daniel J. Abadi* dna@cs.yale.edu † Northwestern Polytechnical University, China * Yale University ABSTRACT Locking is widely used as a concurrency control mechanism in database systems. As more OLTP databases are stored mostly or entirely in memory, transactional throughput is less
CMU SCS 15-721 (Spring 2017) :: Query Compilation
Andy Pavlo / / Carnegie Mellon University / / Spring 2016 ADVANCED DATABASE SYSTEMS Lecture #20 – Query Compilation 15-721 @Andy_Pavlo // Carnegie Mellon University // Spring 2017 CMU 15-721 (Spring 2017) TODAY’S AGENDA Background Code Generation / Transpilation JIT Compilation (LLVM) Real-world Implementations 2 CMU 15-721 (Spring 2017) HEKATON REMARK After switching to an in-memory DBMS, the onl
OLTP Through the Looking Glass, and What We Found There
OLTP Through the Looking Glass, and What We Found There Stavros Harizopoulos HP Labs Palo Alto, CA stavros@hp.com Michael Stonebraker Samuel Madden Daniel J. Abadi Yale University New Haven, CT dna@cs.yale.edu Massachusetts Institute of Technology Cambridge, MA {madden, stonebraker}@csail.mit.edu ABSTRACT Online Transaction Processing (OLTP) databases include a suite of features — disk-resident B-
LogLog-Beta and More: A New Algorithm for Cardinality Estimation Based on LogLog Counting
The information presented in this paper defines LogLog-Beta. LogLog-Beta is a new algorithm for estimating cardinalities based on LogLog counting. The new algorithm uses only one formula and needs no additional bias corrections for the entire range of cardinalities, therefore, it is more efficient and simpler to implement. Our simulations show that the accuracy provided by the new algorithm is as
NoSQL Databases: a Survey and Decision Guidance
(At the bottom of this page, you find a BibTeX reference to cite this article.) Together with our colleagues at the University of Hamburg, we — that is Felix Gessert, Wolfram Wingerath, Steffen Friedrich and Norbert Ritter — presented an overview over the NoSQL landscape at SummerSOC’16 last month. Here is the written gist. We give our best to convey the condensed NoSQL knowledge we gathered build
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https://people.cs.umass.edu/~ramesh/Site/PUBLICATIONS_files/AGSDS2009.pdf
An Empirical Evaluation of In-Memory Multi-Version Concurrency Control
Verifying Strong Eventual Consistency in Distributed Systems
https://arxiv.org/pdf/1509.05053
Microsoft PowerPoint - dbarchVLDB04_concise.ppt
https://research.cs.wisc.edu/multifacet/papers/vldbj02_pax.pdf
https://infoscience.epfl.ch/record/170505/files/aether-smpfulltext.pdf
Hekaton: SQL Server's Memory-Optimized OLTP Engine
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SingleStoreDB Cloud · SingleStore Documentation
Top 5 ScyllaDB Blog Posts from 2016
Computer Sciences
http://www.vldb.org/pvldb/vol9/p1401-chen.pdf