Achieving Sub-ms Latencies on Large Datasets in Public Clouds

YugabyteDB's DocDB storage engine is capable of handling very high data densities per node, which helps keep server footprint and cloud provider bills low. The system was tested on a 4-node cluster in Google Compute Platform with a total data set size of approximately 1.4TB across 300-byte key values and 50-byte value sizes. The results showed that YugabyteDB achieved sub-ms read latencies, with an average read latency of 0.88 ms, and an optimal number of disk I/Os for the workload. This is made possible by Yugabyte's highly optimized storage engine, which effectively chunks/partitions and caches index and bloom filter blocks. The system also demonstrated high bloom filter efficiency in minimizing the number of I/Os to SSTable files in its Log-Structure-Merge organized storage engine.

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