ASE Data Compression Techniques
Today, enterprises are capturing, managing, and utilizing more data than at any time in history. Although traditional relational data is a big contributor to this expansion, there are also new classes of unstructured and semi-structured information that must be taken into consideration. Caring for all of this data is straining the human capital and technology budgets of many organizations.
In response, technology vendors have come up with a number of techniques to squeeze more from existing hardware, software, and network investments. Examples of these improvements include virtualization, parallel processing, and compression. Of these three advances, compression is one of the most effective, yet least disruptive ways to cope with these new challenges. Sybase Adaptive Server Enterprise (ASE) offers a number of complementary compression and other data storage savings methods 1 that have proven to be very effective.
In this paper, we itemize the full range of ASE’s compression techniques for conventional data along with newer classes of unstructured and semi-structured data. For each compression procedure, we’ll describe its architecture, point out common usage scenarios, and provide some sample benchmark proof-points.
The intended audience includes IT management, architects, database administrators, and anyone curious about compression’s role in modern database environments.
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