Implementing data compression techniques in database systems to enhance storage optimization

Borkar, Pradnya

doi:10.47974/jios-2273

Implementing data compression techniques in database systems to enhance storage optimization

2026-05-01

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Borkar, Pradnya

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Patil, Sulabha Narendra *

Shirkande, Shrinivas T.

DOI：10.47974/jios-2273

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ma The huge amount of digital data that is being created every second has made it hard , e g h Enco ing for computer systems to store, run, and keep up with. Using perfect compression methods is a good way to get the most out of your resources while keeping the purity of your data. This research looks at how Huffman coding, LZW, and Run-Length Encoding can be used together in database storage systems. Formulations, theories, and arguments in mathematics set limits on performance and measure how efficient something is. Experiments show that this method saves a lot of space and makes queries faster, especially for bigger datasets. Findings show that systems that can compress data make them scalable, cost-effective, and long-lasting.

Keywords:

Data compression

Database systems

Storage optimization

Huffman

LZW

Run-length encoding

Implementing data compression techniques in database systems to enhance storage optimization

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