MIT, "Relational Cloud: A Database-as-a-Service for the Cloud," CIDR, 2011. [PDF]

Divyakant Agrawal, Amr El Abbadi, Sudipto Das, Aaron J. Elmore, "Database Scalability, Elasticity, and Autonomy in the Cloud," DASFAA, 2011. [PDF]

Relational Cloud

The key idea of the Relational Cloud project is to define the concept of transactional Database-as-a-Service (DBaaS), identify the key challenges toward … Continue Reading ››

Wyatt Lloyd, Michael J. Freedman, Michael Kaminsky, and David G. Andersen, "Don’t Settle for Eventual: Scalable Causal Consistency for Wide-Area Storage with COPS," SOSP, 2011. [PDF]

Summary

This paper introduces a new consistency model, causal+, that extends the causal consistency model and lies between sequential and causal consistency models. The authors claim that causal+ is the … Continue Reading ››

Yahoo! Research, "PNUTS: Yahoo!’s Hosted Data Serving Platform," PVLDB, 2008. [PDF]

Summary

PNUTS is a scalable, highly available, and geographically distributed (but low latency) data store used by most Yahoo! online properties. To achieve both availability and partition tolerance, it uses a novel notion of consistency called per-record timeline consistency; under this model, all replicas of … Continue Reading ››

Microsoft, "DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language," OSDI, 2008. [PDF]

Google, "FlumeJava: Easy, Efficient Data-Parallel Pipelines," PLDI, 2010. [LINK]

Background

Data-parallel computing systems expose high-level abstractions to the users to reason about distributed computations, while handling low-level tasks of scheduling and automated fault-tolerance without any user input. At … Continue Reading ››

Amazon, "Dynamo: Amazon's Highly Available Key-value Store," SOSP, 2007. [PDF]

Summary

Dynamo is a highly available (99.9th percentile) key-value storage mechanism that sacrifices traditional consistency models for eventual consistency to achieve availability. Dynamo works with a simple query model, where read/write (get() and put()) operations are performed on data items uniquely identified by their keys. … Continue Reading ››

Google, "Bigtable: A Distributed Storage System for Structured Data," OSDI, 2006. [PDF]

Summary

Bigtable is a large-scale (petabytes of data across thousands of machines) distributed storage system for managing structured data. It is built on top of several existing Google technology (e.g., GFS, Chubby, and Sawzal) and used by many of Google's online … Continue Reading ››

Michael Armbrust, Armando Fox, David A. Patterson, Nick Lanham, Beth Trushkowsky, Jesse Trutna, Haruki Oh, "SCADS: Scale-Independent Storage for Social Computing Applications," CIDR, 2009. [PDF]

Summary

SCADS (Scalable Consistency Adjustable Data Storage) is a proposal for a collection of components leveraging database, control theory, and machine learning techniques to achieve data scale independence for rapidly … Continue Reading ››