LZ4 data compression algorithm is the current state-of-art compression algorithm in the high speed compression algorithm class, and has been adopted and integrated by lots modern high-speed data storage systems. We propose a fast lossless compression algorithm, named LZ4r. A new format of the data sequence is designed, and by integrating it into the proposed algorithm, a better compression ratio than LZ4 is achieved. Numerous evaluation tests are conducted with different sets of data corpus. The results consistently show that LZ4r gains a significant improvement in compression ratio than LZ4, with a similar high compression speed. Although LZ4r is slower than LZ4 in decompression speed, the decompression speed of LZ4r is still fast enough not to reduce the overall performance of the system. Thus, LZ4r can become a practical and competitive alternative or replacement of LZ4 in many high-speed data storage systems to improve the overall performance and lower the overall cost. More details about LZ4r algorithm design and performance evaluation can be found at [1].

We propose a high-speed lossless data compression algorithm, named SnappyR. Improved upon Snappy, we design new structures of the literal and the match tokens to achieve better compression ratio than Snappy. Numerous benchmarks are conducted on different sets of data corpus. The evaluations consistently show that SnappyR provides a better compression ratio comparing to Snappy, as well as LZ4, and better than LZO in most cases. Although a little slower than Snappy, the compression and decompression speeds of SnappyR are still much higher than entropy encoding based compression algorithms, such as ZSTD, deflate or Zlib. Thus, SnappyR can become another viable replacement or alternative to Snappy, LZ4 or LZO for computing and storage systems and applications, where high-speed lossless data compression is needed. More details about SnappyR algorithm design and performance evaluation can be found at [1].