One fundamental task of wireless sensor networks (WSNs) is to collect useful information from the sensory field and answer users' queries. In order to make effective use of the gigantic amount of individual sensor readings, it is essential to equip WSNs with scalable and energy-efficient data gathering mechanisms. Distinct characteristics of WSNs, e.g., large node density, unattended operation mode, high dynamicity and severe resource constraints, pose a number of design challenges on sensor data gathering schemes. An ever-increasing number of research activities have been carried out on this fundamental and attractive research issue. In this paper, we survey some existing solutions, with an emphasis on four data-centric storage-based methods, i.e., Geographic Hash Table (GHT), Distributed Index for Multi-dimensional range query (DIM), double ruling information brokerage, and landmark-based information storage and retrieval, which cover a range of design choices. We comparatively discuss advantages and disadvantages of the four schemes in detail, in accordance with several important design factors including communication overhead, communication hotspots, fault-tolerance and query locality. We seek to present advances on the topic, to trigger new ideas and to help extend existing techniques to increasingly complicated future protocols.