Data Hub: a hosted platform for organizing, managing, sharing, collaborating and making sense of data

DataHub is a (GitHub like) hosted platform for organizing, managing, sharing, collaborating, and making sense of data. It provides an efficient platform and easy to use tools/interfaces for: Publishing of your own data (hosting, sharing, collaboration) Using other’s data (querying, linking) Making sense of data (analysis, visualization)... (See More)

MapD: a super fast GPU database for visualizing and interacting with Big Data

MapD is a super fast GPU databse, that allows for visualization and interaction with Big Data in real time. Map-D can query, analyze and visualize billions of data points in milliseconds... (See More)

The SPRAWL Distributed Stream Processing System

SPRAWL is a stream processing system designed to address the wide-area data processing and dissemination problem. It allows users to pose SQL-like queries over distributed data streams and execute them efficiently. SPRAWL provides two key functions:
1.  It is able to generate a shared and distributed multi-query plan that transmits records through the network just once

ScalaR: A User Study

Modern database management systems (DBMS) have been designed to efficiently store, manage and perform computations on massive amounts of data. In contrast, many existing visualization systems do not scale seamlessly from small data sets to enormous ones. We have designed a three-tiered visualization system called ScalaR to deal with this issue. ScalaR dynamically performs resolution reduction when the expected result of a DBMS query is too large to be effectively rendered on existing screen real estate.

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