XOR-based compression

Floating point numbers are usually more difficult to compress than integers. Fixed-length integers often have leading zeroes, but floating point numbers usually use all of their available bits, especially if they are converted from decimal numbers, which can't be represented precisely in binary.

Techniques like delta-encoding don't work well for floats, because they do not reduce the number of bits sufficiently. This means that most floating-point compression algorithms tend to be either complex and slow, or truncate significant digits. One of the few simple and fast lossless floating-point compression algorithms is XOR-based compression, built on top of Facebook's Gorilla compression.

XOR is the binary function exclusive or. In this algorithm, successive floating point numbers are compared with XOR, and a difference results in a bit being stored. The first data point is stored without compression, and subsequent data points are represented using their XOR'd values.

Data-agnostic compression

For values that are not integers or floating point, TimescaleDB uses dictionary compression.