With the emergence of novel computing techiniques and applications, the traditional database manamgement systems face challenges, and undergo significant shifts from the single data model processing to multiple data model processing. This paper presents a comphrensive survey on the recent progress and future direction in the novel data management systems, including distributed databases, graph databases, streaming databases, spatial-temporal databases, and crowdsourcing databases. Specifically, the distributed techinqiues play a key role to improve the scabablity of large scale data processing. Graph data management techniques are driven by the big graph management requirement in applications like social network. Stream data management techiniques are also developed to process dynamic data. Spatial-temporal databases are mainly applied in the management of mobile objects. Last but not least, the processing of multiple sources, hetergonenous and low quality data motivates the advance of crowd-sourcing techniques. This study also surveys other hot research directions and foresees the future work.