NoSQL key-value data stores provide an attractive solution for big data management. With the help of data partitioning and replication, those data stores achieve higher levels of availability, scalability and reliability. Such design choices typically exhibit a tradeoff in which data freshness is sacrificed in favor of reduced access latency. At the replica-level, this tradeoff is primarily shaped by the resource allocation strategies deployed for managing the processing of user queries and replica updates. In this demonstration, we showcase AQUAS: a quality-aware scheduler for Cassandra, which allows application developers to specify requirements on quality of service (QoS) and quality of data (QoD). AQUAS efficiently allocates the available replica resources to execute the incoming read/write tasks so that to minimize the penalties incurred by violating those requirements. We demonstrate AQUAS based on our implementation of a microblogging system.
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