Welcome back.

A few sections back we talked about query optimization, and the examples used mostly fit into the category of what we call OLTP or online transaction processing.

In this section we, are going to talk about a different type of query, which is used as part of a business’ reporting needs or decision support systems. These queries tend to be more expensive to execute as they often read a lot of data and aggregate it. We are of course talking about the category of queries called OLAP.

Traditionally, these two categories of queries have been better served by using different database systems. i.e. the transactions are processed in one technology, and then extracted and loaded into a data warehouse in batch for later processing.

And when we think about a traditional business - this workflow fits in nicely. Overnight, after the business day finishes, a job kicks off to perform the ETL (extract, transform and load) operation.

If we look at businesses today though, they are global and transact 24x7. If we look at retail, one of the hot trends, it is same day or instant local delivery. This makes ETL more burdensome because now you can't instantly report and make decisions on your transactional data.

This is where HTAP enters the picture. It means that you can execute both types of queries on the same database system.