Does an automated cloud data warehouse need partitioning and indexes?

This is a late post inspired by my time at RMOUG Training Days 2018. I attended two RMOUG Training Days presentations about automated cloud data warehouse database systems. The first was about Snowflake. The second was about Oracle’s coming Autonomous Data Warehouse Cloud offering. Both products seem to have the goal of automating as much as possible in a data warehouse database and neither seem to allow users to create indexes or to partition their data in the way they choose.

This raises the obvious question – do you need the ability to create indexes and define your own partitioning scheme in a data warehouse database? I have seen many situations on data warehouse databases where both are helpful. When we went to Exadata there was a push to drop all of our indexes but we did not. Also, we used partitioning to improve query performance. If we had to get rid of both features what would we have done on Exadata?

I don’t know the answer, but people say that we need more automation and less control. So, you could spin up a cloud based data warehouse database quickly and start using it. But how many knobs are left to turn when performance is slow? Do users need indexes and partitioning methods to get acceptable performance? Really, what is wrong with giving users the ability to create indexes and to partition tables in the way they want?

Time will tell whether index and partition free cloud based data warehouse database systems make it. But, for now I’m left to wonder what we are losing without these features.


About Bobby

I live in Chandler, Arizona with my wife and three daughters. I work for US Foods, the second largest food distribution company in the United States. I have worked in the Information Technology field since 1989. I have a passion for Oracle database performance tuning because I enjoy challenging technical problems that require an understanding of computer science. I enjoy communicating with people about my work.
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