This paper presents a lossless double-precision floating point compression algorithm. Floating point compression can reduce the cost of storing and transmitting large amounts of data associated with big data problems. A previous algorithm called FPC performs well and uses predictors. However, predictors have limitations. Our program (fzip) overcomes some of these limitations. fzip has 2 phases, first BWT compression, second value and prefix compression with variable length arithmetic encoding. This approach has the advantage that the phases work together and each phase compresses a different type of pattern. On average fzip achieves a 20% higher compression ratio than other algorithms.