Home-grown PCIE SSD VM vs. Azure (Update 12/7)

More testing today with larger database, multiplied the number of rows by 10x up to 1 billion rows in the test dataset.  The latest results indicate I/O about 3 times slower on an Azure D13 server using similar CPU/Ram specs from a dedicated VM on a Gen-1 raid Fusion-io duo drive. Also, the time to insert the test record set was about 2.5 times slower.  This aligns with the performance metrics outlined by http://azure.microsoft.com/blog/2014/10/06/d-series-performance-expectations/. The D series scales upward in terms of SSD capability, so the only way to achieve the I/O of the VM would be to upgrade to a D14 configuration with 800 GB SSD. Along with that comes more cores and memory (16 cores and 112 GB RAM) but that should not significantly affect the I/O comparison.

Here are the bottom line backup logs:

From the dedicated VM (48GB RAM, 6 cores @ 2.66, Dell-branded Fusion-io 640 GB MLC card:

Processed 1931504 pages for database ‘TestDb’, file ‘TestDb’ on file 1.
100 percent processed.
Processed 9 pages for database ‘TestDb’, file ‘TestDb_log’ on file 1.
BACKUP DATABASE successfully processed 1931513 pages in 26.102 seconds (578.114 MB/sec).

From the Azure D13 server (56 GB RAM, 8 Cores @ 2.20 GHz, 400 GB SSD)

Processed 1931648 pages for database ‘TestDb’, file ‘TestDb’ on file 1.
100 percent processed.
Processed 9 pages for database ‘TestDb’, file ‘TestDb_log’ on file 1.
BACKUP DATABASE successfully processed 1931657 pages in 81.958 seconds (184.131 MB/sec).

I’m going to come up with some more tests to perform such as how long it takes to provision a VM from scratch, how long to provision from an image, boot up times, and other metrics that are significant for somebody who wants to be able to quickly provision VMs. I’ll compare these with the times from the colocation environment. This will be posted in a new article.

Here is the configuration I am running on Azure, running the server hasn’t been too expensive yet, used about 5$.00 in last 24 hours, but only put a load on for a few minutes.

image

These are the main findings to this point:

1) For all but a basic/small SQL database in the Azure environment, customers will probably want to utilize the ‘D’ type configuration with the SSD option as this improves performance by a factor of at least 5.

2) Even with the SSD option, the I/O is still 2 – 3 times slower than simply storing a VM or at least the drive with the SQL data on a gen-1 fusion-IO card.

As these offerings mature to allow SSD storage to be enabled for fault-tolerance with larger sizes and higher performance, the standard D offerings will become more appealing for larger customers. It would be helpful if more robust I/O capability could be had without the expense for additional cores as databases tend to get bottlenecked by I/O well below they hit the CPU bottlenecks.

Azure is a great environment to create virtual machines quickly and test out things. But the ‘A’ series is hard to justify as a database solution even for a virtual machine provisioned with 8 cores and 56 GB RAM with a cost of over $1,000 to run over a month. I also have a virtual machine configured on one of my servers at a colocation running SQL Server utilizing PCIE SSD with Fusion-IO storage. The ‘ VM is configured with a similar number of cores and 64 GB of RAM. I created two identical databases with a two tables of 10 million rows.  After building out the data, I tested the SQL backup using the data compression option on both.

Here are the results for the ‘A’ type Azure VM side by side to the results of my VM on PCIE SSD. My performance beat the Azure Enterprise SQL VM with comparable cores and memory by 16x (685 MB/s vs. 39 MB/s and 4 seconds versus 64 seconds). SQL is all about the I/O.

imageimage

Advertisements
This entry was posted in Azure, Cloud, SQL Server and tagged , , . Bookmark the permalink.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s