CDB

Crowd-powered database systems can leverage the crowd's ability to address machine-hard problems, e.g., data integration. Existing crowdsourcing systems adopt the traditional tree model to select a good query plan. However, the tree model can optimize the I/O cost but cannot optimize the monetary cost, latency and quality, which are three important optimization goals in crowdsourcing. To address this limitation, we demonstrate CDB, a crowd-powered database system. CDB proposes a new graph-based model that adopts a fine-grained tuple-level optimization model which significantly outperforms existing coarse-grained tree-based optimization models. Moreover, CDB provides a unified framework to simultaneously optimize the monetary cost, quality and latency. We have deployed CDB on well-known crowd-sourcing platforms and users can easily use our system to deploy their applications. We will demonstrate how to use CDB to address real-world applications, including web table integration and entity collection.