Relational Database Compression Using Augmented Vector Quantization*t

Data compression is one way to alleviate the 1/0 bot-tleneck problem faced by I/O-intensive applications such as databases. However, this approach is not widely used because of the lack of suitable database compression techniques. In this paper, we design and implement a novel database compression technique based on vector quantization (VQ). VQ is a data com-pression technique with wide applicability in speech and image coding [3, 51, but it is not directly suit-able for databases because it is lossy. We show how one may use a lossless version of vector quantization to reduce database space storage requirements and im-prove disk I/O bandwidth.