Open Source Analytics

MySQL makes an obvious and affordable choice for data warehousing. Its traditional weaknesses (from OLTP system point of view) are actually its strengths when it comes to Data warehousing and OLAP.

If you look at the requirements from a DW, you’d see that unlike OLTP systems, transactions are not required, and 60×24x7 uptimes are not really needed. On the contrary the system should be able to handle queries most efficiently and should provide capabilities for high-speed bulk loading in batch jobs. This is where MySQL shines over competition. (more…)

So how is a data warehouse different from your regular database? After all, both are databases, and both have some tables containing data. If you look deeper, you’d find that both have indexes, keys, views, and the regular jing-bang. So is that ‘Data warehouse’ really different from the tables in you application? And if the two aren’t really different, maybe you can just run your queries and reports directly from your application databases!

Well, to be fair, that may be just what you are doing right now, running some EOD (end-of-day) reports as complex SQL queries and shipping them off to those who need them. And this scheme might just be serving you fine right now. Nothing wrong with that if it works for you.

But before you start patting yourself on the back for having avoided a data warehouse altogether, do spend a moment to understand the differences, and to appreciate the pros and cons of either approach. (more…)