This paper reviews the researches and developments in the last decade on near lossless satellite data compression techniques at the Canadian Space Agency (CSA). After briefly describing the two vector quantization based near lossless hyperspectral data compression techniques, it reviews the activities that assessed the near lossless properties of the compression techniques. The assessment results demonstrated that the compression errors introduced by the compression techniques are smaller than the intrinsic noise of the original data. This level of compression errors is considered as near lossless, as it has no impact or minor impact on the afterwards application utilization comparing the original data. This paper summarizes the activities of evaluating how satellite data product level impacts the compression performance for making decision whether or not on-board data processing is required or radiometric conversion should be applied on-board before compression. These evaluations examined the impact of the anomalies in raw hyperspectral data and the impact of on-board pre-processing and radiometric conversion on compression performance. The studies on the effect of spatial and spectral distortion of hyperspectral sensors on compression performance are also reviewed. This paper summarizes a multi-disciplinary user acceptability study that systematically assessed the impacts of the compression techniques on remote sensing products and applications. Eleven user groups covered a wide range of application areas and a variety of hyperspectral sensors participated in the study. This paper reviews the effort to explore the benefits of employing forward error correction to further enhance the resilience to bit-errors of the compressed data. The hardware developments are reported. Two versions of hardware compressor prototypes that implement the CSA near lossless compression techniques for on-board processing have been built. Finally, this paper reports the CSA's participation in the development of international standards for satellite data systems within the CCSDS organization.