Database management systems (DBMSs) are facing challenges in supporting non-traditional data retrieval for emerging applications. We need retrieval systems over data, much like a "Google" for databases, parallel the well-established information retrieval over text. Such systems should allow users to use flexible and intuitive queries capturing their information needs, and to explore the databases effectively. In the talk, I will discuss this exciting research area and introduce my work in this direction. In particular I will present RankSQL, a DBMS that provides a systematic and principled framework for ranking by extending relational algebra. I will further introduce our work on ranking aggregate queries. Effective data retrieval mechanisms go beyond just ranking. I will discuss our proposal of generalizing Group-By to clustering, parallel to the generalization from Order-By to ranking, and combining the two constructs. Moreover, I will briefly mention our study of inverse ranking queries.