Data Compression plays an important role in the age of information technology. It is now very important a part of everyday life. Data compression has an important application in the areas of file storage and distributed systems. Because real world files usually are quit redundant, compression can often reduce the file sizes considerably, this in turn reduces the needed storage size and transfer channel capacity. This paper surveys a variety of data compression techniques spanning almost fifty years of research. This work illustrates how the performance of data compression techniques is varied when applying on different types of data. In this work the data compression techniques: Huffman, Adaptive Huffman and arithmetic, LZ77, LZW, LZSS, LZHUF, LZARI and PPM are tested against different types of data with different sizes. A framework for evaluation the performance is constructed and applied to these data compression techniques.