Query optimization in compressed database systems
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Querying Compressed Data in Data Warehouses
Information Technology and Management
Block-Oriented Compression Techniques for Large Statistical Databases
IEEE Transactions on Knowledge and Data Engineering
Vector quantization for lossless textual data compression
DCC '95 Proceedings of the Conference on Data Compression
Compression techniques for fast external sorting
The VLDB Journal — The International Journal on Very Large Data Bases
AlphaSum: size-constrained table summarization using value lattices
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Reducing metadata complexity for faster table summarization
Proceedings of the 13th International Conference on Extending Database Technology
External sorting with on-the-fly compression
BNCOD'03 Proceedings of the 20th British national conference on Databases
Query-aware compression of join results
Proceedings of the 16th International Conference on Extending Database Technology
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Data compression is one way to alleviate the I/O bottleneck 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, 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.