The commercialization of CD-ROM drives has clearly demonstrated the ability of optical storage devices to meet the growing demand for archival data storage. However, with the continued expansion of electronic information resources, storage capacity requirements are expected to approach the terabyte level for personal users and exceed the petabyte level for databases and data warehouse systems. Further, many data-intensive applications require real-time data access rates. Thus, designers for the next generation of archival storage systems have the challenging task of providing storage capacities several orders of magnitude larger than existing systems while maintaining current data access times. To meet this challenge, we have developed a single-chip database filter suitable for large-capacity database systems that use page-oriented optical storage devices. Based on a photonic VLSI device technology, our data filter monolithically integrates optical detectors, photoreceiver circuits, data manipulation logic, and filter control circuitry onto a single CMOS chip that can be readily fabricated using a standard VLSI fabrication facility. Thus, our device is compatible with existing electronic device manufacturing technology and shares all of the reliability, uniformity, and manufacturability benefits associated with current electronic hardware. In addition to describing the database filter concept, this paper presents design and circuit evaluation data suggesting that a 32x32-bit filter fabricated in a 1.5-?m CMOS process could have an optical page read rate of 87 Mpage/s and support 123-Mrecord/s transfer rate to a host computer. Finally, queuing theory is used to show that even with the limitation of finite queue capacity, a database filter chip could be controlled to work at near-optimal performance, where database search time is limited by the data transfer rate into the host computer. Since only valid search data are passed through to the host computer, the introduction of a database filter can dramatically reduce database search time.