How SHOPLINE Saves 40% Space in Main Database, Part 2

An in-depth guide to practical data tiering and advanced technical solutions

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• Part 1: Data tiering methodology
• Part 2 (this article): Practice detail

If you haven’t read Part 1 yet, we suggest you start there. In Part 1 we went through the complete steps of how to start data tiering from the business side.

Let’s quickly review the process from the previous article.

1. Identify the target that needs to be tiered.
2. Set the time partitioning for data tiering to occur.
3. Define the user scenarios for the cold data.
4. Verify our hypothesis.
5. Make the right technical selection.
6. Begin implementation.

When SHOPLINE decides to perform data tiering, based on the above process, we need to know which target to start with first.

After actually counting all the tables, we found that the order related data takes up more than 80% of the main database capacity, and among them, the order and its metadata are the most significant.