Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Prashanth Menon"'
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:3867-3882
Due to recent explosion of data volume and velocity, a new array of lightweight key-value stores have emerged to serve as alternatives to traditional databases. The majority of these storage engines, however, sacrifice their read performance in order
Autor:
William Zhang, Dana Van Aken, Matthew Butrovich, Andrew Pavlo, Prashanth Menon, Lin Ma, Wan Shen Lim
Publikováno v:
Proceedings of the VLDB Endowment. 14:3211-3221
Database management systems (DBMSs) are notoriously difficult to deploy and administer. Self-driving DBMSs seek to remove these impediments by managing themselves automatically. Despite decades of DBMS auto-tuning research, a truly autonomous, self-d
Autor:
Alexander Behm, Shoumik Palkar, Utkarsh Agarwal, Timothy Armstrong, David Cashman, Ankur Dave, Todd Greenstein, Shant Hovsepian, Ryan Johnson, Arvind Sai Krishnan, Paul Leventis, Ala Luszczak, Prashanth Menon, Mostafa Mokhtar, Gene Pang, Sameer Paranjpye, Greg Rahn, Bart Samwel, Tom van Bussel, Herman van Hovell, Maryann Xue, Reynold Xin, Matei Zaharia
Publikováno v:
Proceedings of the 2022 International Conference on Management of Data.
Autor:
Andrew Pavlo, Prashanth Menon, Amadou Ngom, Todd C. Mowry, Matthew Butrovich, Lin Ma, Wan Shen Lim
Publikováno v:
DaMoN
Advances in memory technology have made it feasible for database management systems (DBMS) to store their working data set in main memory. This trend shifts the bottleneck for query execution from disk accesses to CPU efficiency. One technique to imp
Publikováno v:
ICDE
Due to the recent explosion of data volume and velocity, a new array of lightweight key-value stores have emerged to serve as alternatives to traditional databases. The majority of these storage engines, however, sacrifice their read performance in o
Publikováno v:
Proceedings of the VLDB Endowment. 11:1-13
In-memory database management systems (DBMSs) are a key component of modern on-line analytic processing (OLAP) applications, since they provide low-latency access to large volumes of data. Because disk accesses are no longer the principle bottleneck
Autor:
Mathew Philip, Prakash Zacharias, Shibi Mathew, Prashanth Menon, Maya Pithambaran, Akshay Jayaprakash, Sandeep V. Kumbar, Akshay Deshpande, Aby Somu, Sudarshan Patil, John Mathews
Publikováno v:
Journal of Clinical and Experimental Hepatology. 8:S78-S79
Publikováno v:
SIGMOD Conference
Data-intensive applications seek to obtain trill insights in real-time by analyzing a combination of historical data sets alongside recently collected data. This means that to support such hybrid workloads, database management systems (DBMSs) need to
Publikováno v:
Endoscopy. 48:E378-E379
Autor:
Sudarshan Patil, Shibi Mathew, Akshay Jayaprakash, Sandeep V. Kumbar, Aby Somu, Maya Peethambaran, John Mathews, Prashanth Menon, Akshay Deshpande, Prakash Zacharias, Mathew Philip
Publikováno v:
Journal of Clinical and Experimental Hepatology. 8:S75