As extracellular electrode arrays with 100 or more active recording sites become more widely used for simultaneous recording of neural ensembles, practical data acquisition systems that can efficiently accommodate high electrode counts are needed. To reduce the high data rates associated with extracellular recordings from these arrays, various algorithms and systems have been designed to provide complete online detection and classification of extracellular spike waveforms. However, many of these algorithms require significant user supervision to ensure accurate performance. In this paper, we discuss the design and validation of a 100-channel PC-based system that can be used with arrays of extracellular electrodes such as the Utah Electrode Array. Instead of comprehensive online spike analysis, the system performs online detection and storage of the spike waveforms for offline classification. This strategy preserves the data of interest, reduces system complexity, and requires less user supervision during experiments.