As LiDAR sensors have become ubiquitous, the need for an efficient LiDAR data compression algorithm has increased. Modern LiDARs produce gigabytes of scan data per hour (Fig. 1) and are often used in applications with limited compute, bandwidth, and storage resources. We present a fast, lossless compression algorithm for Li-DAR range and attribute scan sequences including multiple-return range, signal, reflectivity, and ambient infrared. Our algorithm—dubbed “Jiffy”—achieves substantial compression by exploiting spatiotemporal redundancy and sparsity. Speed is accomplished by maximizing use of single-instruction-multiple-data (SIMD) instructions. In autonomous driving, infrastructure monitoring, drone inspection, and handheld mapping benchmarks, the Jiffy algorithm consistently outcompresses competing lossless codecs while operating at speeds in excess of 65M points/sec on a single core. In a typical autonomous vehicle use case, single-threaded Jiffy achieves 6x compression of centimeter-precision range scans at 500+ scans per second. To ensure reproducibility and enable adoption, the software is freely available as an open source library33Software is available here: http://github.com/jsford64/jiffy-compression.