Abstract
| Original language | English (US) |
|---|---|
| Number of pages | 2 |
| State | Published - 2015 |
| Event | Eighth Annual New England Database Day - Massachusetts Institute of Technology, Cambridge, MA, United States Duration: Jan 30 2015 → Jan 30 2015 http://db.csail.mit.edu/nedbday15/ |
Conference
| Conference | Eighth Annual New England Database Day |
|---|---|
| Abbreviated title | NEDB Day |
| Country | United States |
| City | Cambridge, MA |
| Period | 1/30/15 → 1/30/15 |
| Internet address |
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The BigDawg Architecture and Reference Implementation. / Duggan, Jennie M; Elmore, Aaron J.; Kraska, Tim; Madden, Sam; Mattson, Tim; Stonebraker, Michael.
2015. Paper presented at Eighth Annual New England Database Day, Cambridge, MA, United States.Research output: Contribution to conference › Paper
TY - CONF
T1 - The BigDawg Architecture and Reference Implementation
AU - Duggan, Jennie M
AU - Elmore, Aaron J.
AU - Kraska, Tim
AU - Madden, Sam
AU - Mattson, Tim
AU - Stonebraker, Michael
PY - 2015
Y1 - 2015
N2 - This paper presents the reference implementation of a new architecture for future “Big Data” applications. Such applications require “big analytics” as one might expect, but they also require real-time streaming support, real-time analytics, data visualization, and cross-storage queries. We are guided by the principle “one size does not fit all”, and we build on top of three storage engines, each designed for specialized use cases. In addition, we demonstrate novel support for querying across multiple storage engines as well as pioneering solutions to data visualization. In the remainder of this short paper, we describe the first of three BigDawg reference implementations, Bulldog. In the next two years we expect to follow with Pitbull and Rottweiler releases.
AB - This paper presents the reference implementation of a new architecture for future “Big Data” applications. Such applications require “big analytics” as one might expect, but they also require real-time streaming support, real-time analytics, data visualization, and cross-storage queries. We are guided by the principle “one size does not fit all”, and we build on top of three storage engines, each designed for specialized use cases. In addition, we demonstrate novel support for querying across multiple storage engines as well as pioneering solutions to data visualization. In the remainder of this short paper, we describe the first of three BigDawg reference implementations, Bulldog. In the next two years we expect to follow with Pitbull and Rottweiler releases.
M3 - Paper
ER -