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Compression can sometimes improve performance by making more of the dataavailable to the processors faster. We consider the compression of integer keysin a B+-tree index. For this purpose, systems such as IBM DB2 use variable-bytecompression over differentially coded keys. We revisit this problem withvarious compression alternatives such as Google's VarIntGB, Binary Packing andFrame-of-Reference. In all cases, we describe algorithms that can operatedirectly on compressed data. Many of our alternatives exploit thesingle-instruction-multiple-data (SIMD) instructions supported by modern CPUs.We evaluate our techniques in a database environment provided by Upscaledb, aproduction-quality key-value database. Our best techniques are SIMDaccelerated: they simultaneously reduce memory usage while improvingsingle-threaded speeds. In particular, a differentially coded SIMDbinary-packing techniques (BP128) can offer a superior query speed (e.g., 40%better than an uncompressed database) while providing the best compression(e.g., by a factor of ten). For analytic workloads, our fast compressiontechniques offer compelling benefits. Our software is available as open source.

Upscaledb: Efficient Integer-Key Compression in a Key-Value Store using SIMD Instructions