Sql server data file raid

The max uncached disk IOPS and throughput is the maximum remote storage limit that the virtual machine can handle. This limit is defined at the virtual machine and is not a limit of the underlying disk storage. The amount of uncached IOPS and throughput that is available for a VM can be verified in the documentation for your virtual machine. This limit is governed at the virtual machine level regardless of the underlying premium disk storage.

For more information, see uncached and cached limits. The max cached and temp storage throughput limit is a separate limit from the uncached throughput limit on the virtual machine. The Azure BlobCache consists of a combination of the virtual machine host's random-access memory and locally attached SSD. When caching is enabled on premium storage, virtual machines can scale beyond the limitations of the remote storage uncached VM IOPS and throughput limits.

Only certain virtual machines support both premium storage and premium storage caching which needs to be verified in the virtual machine documentation. For example, the M-series documentation indicates that both premium storage, and premium storage caching is supported:. The limits of the cache will vary based on the virtual machine size. You can manually enable host caching on an existing VM. Stop all application workloads and the SQL Server services before any changes are made to your virtual machine's caching policy.

Changing any of the virtual machine cache settings results in the target disk being detached and reattached after the settings are applied. Your storage caching policy varies depending on the type of SQL Server data files that are hosted on the drive.

The following table provides a summary of the recommended caching policies based on the type of SQL Server data:. Changing the cache setting of an Azure disk detaches and reattaches the target disk. When changing the cache setting for a disk that hosts SQL Server data, log, or application files, be sure to stop the SQL Server service along with any other related services to avoid data corruption. To learn more, see Disk caching. Analyze the throughput and bandwidth required for your SQL data files to determine the number of data disks, including the log file and tempdb.

Throughput and bandwidth limits vary by VM size. To learn more, see VM Size. Add additional data disks and use disk striping for more throughput.

To configure disk striping, see disk striping. There are throughput limits at both the disk and virtual machine level. Applications that consume resources beyond these limits will be throttled also known as capped. Select a virtual machine and disk size in a disk stripe that meets application requirements and will not face capping limitations.

To address capping, use caching, or tune the application so that less throughput is required. Virtual machines configured to scale up during times of high utilization should provision storage with enough IOPS and throughput to support the maximum VM size while keeping the overall number of disks less than or equal to the maximum number supported by the smallest VM SKU targeted to be used.

The following illustration summarizes the results of the previous example except for the Filestream data. Filegroups use a proportional fill strategy across all the files within each filegroup.

As data is written to the filegroup, the SQL Server Database Engine writes an amount proportional to the free space in the file to each file within the filegroup, instead of writing all the data to the first file until full.

It then writes to the next file. For example, if file f1 has MB free and file f2 has MB free, one extent is given from file f1, two extents from file f2, and so on. In this way, both files become full at about the same time, and simple striping is achieved. For example, a filegroup is made up of three files, all set to automatically grow.

When space in all the files in the filegroup is exhausted, only the first file is expanded. When the first file is full and no more data can be written to the filegroup, the second file is expanded. When the second file is full and no more data can be written to the filegroup, the third file is expanded.

If the third file becomes full and no more data can be written to the filegroup, the first file is expanded again, and so on. For more information on transaction log file management recommendations, see Manage the size of the transaction log file. Skip to main content. This browser is no longer supported. Download Microsoft Edge More info. Contents Exit focus mode. Is this page helpful?

Please rate your experience Yes No. Any additional feedback? Submit and view feedback for This product This page. View all page feedback. Edit: we definitely want redundancy on a production server, so RAID 0 by itself is out. RAID 10 is nice, but might be a bit expensive for us. When you write data to a RAID 1 array, it has to write that data to both disks, so you do not gain any performance increase, however this is where you get your data security.

When reading from a RAID 1 array the controller will read from both disks as they have the same data on them. This is useful for protecting larger amounts of data. If you want to protect gb in with RAID 5 you can achieve that with 4xgb drives or 3xgb drives, requiring gb of total purchased drive space.

Offers similar advantages as RAID 1 taking it up another notch with the striping across disks. You will be processing multiple queries at once and so the striping isn't going to help as much.

This was on a much larger scale a 20 disk and 16 disk SAN but same concepts. I'd spend a little time making sure your database is efficiently indexed; monitor it for Full Table Scans, make sure the most frequent queries read as little data as possible; I'd take an efficiently designed database on a slow disk setup over a database with improper indexes on SSDs. Be aware that the key performance metric will be the seek rate, not the data rate.

That is, a typical database that is disk-bound as yours may become as it grows will be limited by how many IOs per second the disks can support, rather than the maximum data rate they can support for sequential reads.

Of course, you won't get as much usable storage out of the two RAID1 pairs. Given the small size of the database I would use four 15krpm 2. I'd put the data on one array and the logs on another for safety. The theory is RAID 1 gives you two drives for a read, but dont' think that equals two times the performance. As a matter of fact, it doesn't, usually the sequential read spee ends up being exactly the same as one drive. Surprising, but true I would have some small OS partition on one of them, but definately give both raids to sql server for data.

Give sql server all the sets you can. That way if any individual disk fails, its clone will take over processing, and the user never knows a failure occured. RAID 1 does have a performance penalty for writes. Each write IOP has to be performed twice you have to write every piece of data to two disks.

Reads however can be sped up because the controller can actually read from both disks in a mirror set at the same time in order to serve a large Read request. It provides the performance advantages of Striping RAID 0 , and then adds a degree of fault tolerance by using what's called Parity.

Parity is data that is calculated and stored so that if a disk in the array fails, the parity data can be used to rebuild the data that was in the lost disk. Although parity is great for fault tolerance, it is expensive from a performance standpoint.

RAID 5 has a write penalty of 4x. There is a Write penalty in that each value must be written to the Mirror Disk as well for fault tolerance but still, the perfomance is incredibly fast.

For the sake of this paper, we will assume that they are the same. Some of them reserve 1 disk in the RAID Array to store parity data on, some of them stripe the parity data across the disks, etc etc etc. DP stands for "Dual Parity". It is similar to RAID 5 except it writes the parity data twice. Depending on how much money you spend on the RAID Controller, you typically are given more configuration options.

Caching can be configured to cache Read activity, Write Activity, or in some cases both. Caching is very important for SQL Server, especially for writes. The writes are where we incure performance penalties. This can improve write performance dramatically. Typically the RAID controllers that allow for Write Caching will have a battery backed cache system so that if power goes out in the middle of a write, the battery backup will ensure that the data in cache makes it to disk before total failure.

Rember, SQL Server itself is very good at caching reads also. On other consideration you'll want to think about is virtualization. Whether we like it or not, we are moving to a virtualized world.