Demo Data from EDBT 2026 / reviewers in the wild / expert
Karthik Ranganathan
dblp:85/387
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
1 paper |
Distributed and cloud data management · 77% Database system architecture and tuning · 23% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 50% Hardware reliability and fault tolerance · 50% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed systems
consistency and availability tradeoff |
0.0 | 1 | 2011 | Apache hadoop goes realtime at Facebook · SIGMOD Conference 2011 |
Hardware reliability and fault tolerance › network fault tolerance
network partition tolerance |
0.0 | 1 | 2011 | Apache hadoop goes realtime at Facebook · SIGMOD Conference 2011 |
Methods — techniques the papers use, named apart from their topics
system configuration tuning · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Apache hadoop goes realtime at FacebookabstractFacebook recently deployed Facebook Messages, its first ever user-facing application built on the Apache Hadoop platform. Apache HBase is a database-like layer built on Hadoop designed to support billions of messages per day. This paper describes the reasons why Facebook chose Hadoop and HBase over other systems such as Apache Cassandra and Voldemort and discusses the application's requirements for consistency, availability, partition tolerance, data model and scalability. We explore the enhancements made to Hadoop to make it a more effective realtime system, the tradeoffs we made while configuring the system, and how this solution has significant advantages over the sharded MySQL database scheme used in other applications at Facebook and many other web-scale companies. We discuss the motivations behind our design choices, the challenges that we face in day-to-day operations, and future capabilities and improvements still under development. We offer these observations on the deployment as a model for other companies who are contemplating a Hadoop-based solution over traditional sharded RDBMS deployments. Dhruba Borthakur, Jonathan Gray, Joydeep Sen Sarma, Kannan Muthukkaruppan, Nicolas Spiegelberg, Hairong Kuang, Karthik Ranganathan, Dmytro Molkov, Aravind Menon, Samuel Rash, Rodrigo Schmidt, Amitanand S. Aiyer |
SIGMOD Conference | 7 |
| 2005 | A Novel Memory Structure for Embedded Systems: Flexible Sequential and Random Access Memory
Karthik Ranganathan, Vasudev V. Pai, David J. Lilja, Kia Bazargan |
J. Comput. Sci. Technol. | 2 |