Light fields can be used to generate novel images of a scene as seen through a virtual camera with almost freely configurable parameters. As recording methods and equipment get better over time, the size of typical light fields is growing and the amount of resulting data can pose a challenge. Therefore here, the focus lies on spatially dense light field data with images captured in high resolution. This work aims to evaluate state-of-the-art compression algorithms, namely modern video encoders like the HEVC standard, in their suitability for compressing light field data. It tries to give insights into which encoder and settings to chose for a light field compression task and how to evaluate the choice. To this end, adequate quality metrics to objectively rate the performance of different encoders are chosen. Examined compression algorithms are rated for their performance in a setting, where the size of the light field data has to be reduced, but where it is not a requirement for the compressed data to be in a state that can directly provide random access to individual light field images or light rays. A compression pipeline is implemented and used to evaluate several video encoders under different aspects.