Relational Database Compression Using Augmented Vector Quantization

Data compression is one way to alleviate the 1/0bottleneck 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 compression technique with wide applicability in speech and image coding [3, 51, but it is not directly suitable 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 improve disk I/O bandwidth.

• Type: Conference
• Year: 1995
• Where: ICDE
• Authors: Wee Keong Ng, Chinya V. Ravishankar
• Keywords: Data Compression Technique, Database, Database Compression Technique, ICDE 1995, Suitable Database Compression