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The Software RAID Inflection Point

In June, 2001 something amazing happened in the IT world: Intel released the Tualatin based Pentium IIIS 1.0 GHz processor. This was one of the first few Intel processors (IA32 architecture) to have crossed the 1 GHz clock barrier and the first of any significance. It was also special in that it had dual processor support and a double sized cache compared to its Coppermine based forerunners or it’s non-“S” Tualatin successor (that followed just one month behind.) The PIIIS system boards were insanely popular in their era and formed the backbone of high performance commodity servers, such as Proliant and PowerEdge, in 2001 and for the next few years culminating in the Pentium IIIS 1.4GHz dual processor systems that were so important that they resulted in kicking off the now famous HP Proliant “G” naming convention. The Pentium III boxes were “G1”.

What does any of this have to do with RAID? Well, we need to step back and look at where RAID was up until May, 2001. From the 1990s and up to May, 2001 hardware RAID was the standard for the IA32 server world which mainly included systems like Novell Netware, Windows NT 4, Windows 2000 and some Linux. Software RAID did exist for some of these systems (not Netware) but servers were always struggling for CPU and memory resources and expending these precious resources on RAID functions was costly and would cause applications to compete with RAID for access and the systems would often choke on the conflict. Hardware RAID solved this by adding dedicated CPU and RAM just for these functions.

RAID in the late 1990s and early 2000s was also very highly based around RAID 5 and to a lesser degree, RAID 6, parity striping because disks were tiny and extremely expensive for capacity and squeezing maximum capacity out of the available disks was of utmost priority and risks like URE were so trivial due to the small capacity sizes that parity RAID was very reliable, all things considered. The factors were completely different than they would be by 2009. In 2001, it was still common to see 2.1GB, 4.3GB and 9GB hard drives in enterprise servers!

Because parity RAID was the order of the day, and many drives were typically used on each server, RAID had more CPU overhead on average in 2000 than it did in 2010! So the impact of RAID on system resources was very significant.

And that is the background. But in June, 2001 suddenly the people who had been buying very low powered IA32 systems had access to the Tualatin Pentium IIIS processors with greatly improved clock speeds, efficient dual processor support and double sized on chip caches that presented an astounding leap in system performance literally over night. With all this new power and no corresponding change in software demands systems that traditionally were starved for CPU and RAM suddenly had more than they knew how to use, especially as additional threads were available and most applications of the time were single threaded.

The system CPUs, even in the Pentium III era, were dramatically more powerful than the small CPUs, which were often entry level PowerPC or MIPS chips, on the hardware RAID controllers and the available system memory was often much larger than the hardware RAM caches and investing in extra system memory was often far more effective and generally advantages so with the availability of free capacity on the main system RAID functions could, on average be moved from the hardware RAID cards to the central system and gain performance, even while giving up the additional CPU and RAM of the hardware RAID cards. This was not true on overloaded systems, those starved for resources and was more relevant for parity RAID systems with RAID 6 benefiting the most and non-parity systems like RAID 1 and 0 benefiting the least.

But June, 2001 was the famous inflection point – before that date the average IA32 system was faster when using hardware RAID. And after June, 2001 new systems purchased would on average be faster with software RAID. With each passing year the advantages have leaned more and more towards software RAID with the abundance of underutilized core CPUs and idle threads and spare RAM exploding with the only advantage towards hardware RAID being the drop in parity RAID usage as mirrored RAID took over as the standard as disk sizes increased dramatically while capacity costs dropped.

Today is has been more than fifteen years since the notion that hardware RAID would be faster has been retired. The belief lingers on due primarily to the odd “Class of 1998” effect. But this has long been a myth repeated improperly by those that did not take the time to understand the original source material. Hardware RAID continues to have benefits, but performance has not been one of them for the majority of the time that we’ve had RAID and is not expected to ever rise again.

Logical Volume Managers

A commonly used but often overlooked or misunderstood storage tool is the Logical Volume Manager.  Logical Volume Managers, or LVMs, are a storage abstraction, encapsulation and virtualization technology used to provide a level of flexibility often otherwise unavailable.

Most commonly an LVM is used to replace traditional partitioning systems, and sometimes additional functionality is rolled into an LVM such as RAID functions.  Nearly all operating systems offer an integrated LVM product today and most have for a very long time.  LVMs have become a standard feature of both server and client side storage management.

LVMs do not necessarily offer uniform features but common features often included in an LVM are logical volumes (soft partitioning), thin provisioning, flexible physical location allocation, encryption, simple RAID functionality (commonly only mirror based RAID) and snapshots.  Essentially all LVMs offer logical volumes, snapshots and flexible allocation; these being considered fundamental LVM functions.

Popular LVMs include Logical Disk Management on Windows Server 2000 through Server 2008 R2, Storage Spaces on Windows 2012 and later, LVM on Linux, BtrFS on Linux, Core Storage on Mac OSX, Solaris Volume Manager on Solaris, ZFS on Solaris and FreeBSD, Vinum Volume Manager on FreeBSD, Veritas Volume Manager for most UNIX systems, LVM on AIX and many more.  LVMs have been increasingly popular and standard since the late 1980s.  ZFS and BtrFS are interesting as they are filesystems that implement an LVM inside of the filesystem as an integrated system.

An LVM consumes block devices (drive appearances) and creates logical volumes (often referred to as LVs) which are themselves drive appearances as well.  Because of this, an LVM can sit at any of many different places in the storage stack.  Most commonly we would expect an LVM to consume a RAID array, split one RAID array into one or more logical volumes with each logical volume having a filesystem applied to it.  But it is completely possible for an LVM to sit directly on physical storage without RAID, and it is very possible for RAID to be implemented via software on top of the logical volumes rather than beneath them.  LVMs are also very useful for combining many different storage systems into one such as combining many physical devices and/or RAID arrays into a single, abstracted entity that can then be split up into logical volumes (with single volumes potentially utilizing many different underlying storage devices.)  One standard use of an LVM is to combine many SAN LUNs (potentially from a single SAN system or potentially from several different ones) into a single volume group.

While LVMs provide power and flexibility for working with multiple storage devices and types of storage devices while presenting a standard interface to higher layers in the storage stack, probably the most common usages are to provide for flexibility where rigid partitions used to be and for snapshots.  Traditional partitions are rigid and cannot be resized.  Logical volumes can almost always be grown or shrunk as needed making them tremendously more flexible.

Snapshots have become a major focus of LVM usage in the last decade, although mostly this has happened because of snapshot awareness growing rather than a recent shift in availability.  Commodity virtualization systems have brought snapshots from an underlying, storage industry knowledge component into the IT mainstream.  Much of how virtualization technologies tend to tackle storage virtualization can be thought of as being related to LVMs, but generally this is similar functionality offered in a different manner or simply passing LVM functionality on from a lower layer.

Today you can expect to find LVMs in use nearly everywhere, even implemented transparently on storage arrays (such as SAN equipment) to provide more flexible provisioning.  They are not just standardly available, but standardly implemented and have done much to improve the reliability and capability of modern storage.

Practical RAID Choices for Spindle Based Arrays

A truly monumental amount of information abounds in reference to RAID storage systems exploring topics such as risk, performance, capacity, trends, approaches and more.  While the work on this subject is nearly staggering the information can be distilled into a handful of common, practical storage approaches that will cover nearly all use cases.  My goal here is to provide a handy guide that will allow a non-storage practitioner to approach RAID decision making in a practical and, most importantly, safe way.

For the purposes of this guide we will assume storage projects of no more than twenty five traditional drives (spinning platter drives properly known as Winchester drives.)  These drives could be SFF (2.5″) or LFF (3.5″) commonly, SATA or SAS, consumer or enterprise.  We will not tackle solid state drives as these have very different characteristics and require their own guidance.  Storage systems larger than roughly twenty five spindles should not work from standard guidance but delve deeper into specific storage needs to ensure proper planning.

The guidance here is written for standard systems in 2015.  Over the past two decades the common approaches to RAID storage have changed dramatically and while it is not anticipated that the key factors that influence these decisions will change enough in the future to alter these recommendations it is very possible that they will.  Good RAID design of 1998 is very poor RAID design today.  The rate of change in the industry has dropped significantly since that time and these recommendations are likely to stand for a very long time, very possibly until spindle-based drive storage is no longer available or at least popular, but like all things predictions are subject to great change.

In general we use what is termed a “One Big Array” approach.  That is a single RAID array on which all system and data partitions are created.  The need or desire to split our storage into multiple, physical arrays is mostly gone today and should only be done in non-general circumstances.  Only in situations where careful study of the storage needs and heavy analysis are being done should we look at array splitting.  Array splitting is far more likely to cause harm rather than good.  When it doubt, avoid split arrays.  The goal of this guide is general rules of thumb to allow any IT Pro to build a safe and reliable storage system.  Rules of thumb do not and can not cover every scenario, exceptions always exist.  But the idea here is to cover the vast majority of cases with tried and true approaches that are designed around modern equipment, use cases and needs while being mindful to err on the side of safety – when a choice is less than ideal it is still safe.  None of these choices is at all reckless, at worst they are overly conservative.

The first scenario we should consider is if your data does not matter.  This may sound like an odd thing to consider but it is a very important scenario.  There are many times where data saved to disk is considered ephemeral and does not need to be protected.  This is common for reconstructable data such as working space for rendering, intermediary calculation spaces or caches – situations where spending money to protect data is wasted and it would be acceptable to simply recreate lost data rather than protecting it.  This could be a case where downtime is not a problem and data is static or nearly so and rather than spending to reduce downtime we only worry about protecting the data via backup mechanisms so that if an array fails we simply restore the array completely.  In these cases the obvious choice is RAID 0.  It is very fast, very simple and provides the most cost effective capacity.  The only downside of RAID 0 is that it is fragile and provides no protection against data loss in case of drive failure or even a URE (which would cause data corruption the same as a desktop drive faces.)

It should be noted that an exception to the “One Big Array” approach that would be common is in systems using RAID 0 for data.  There would be a very good argument made for a small drive array dedicated to the OS and application data that would be cumbersome to reinstall in case of array loss being kept on RAID 1 and the RAID 0 data array being separate from it.  This way recovery could be very rapid rather than needing to completely rebuild the entire system from scratch rather than simply recreating the data.

Assuming that we have eliminated cases where the data does not require protection, we will assume for all remaining cases that the data is quite important and we want to protect it at some cost.  We will assume that protecting the data as it exists on the live storage is important, generally because we want to avoid downtime or because we want to ensure data integrity because the data on disk is not static and an array failure would also constitute data loss.  With this assumption we will continue.

If we have an array of only two disks the answer is very simple, we choose RAID 1.  There is no other option at this size, so no decision to be made.   In theory we should be planning our arrays holistically and not after the number of drives is determined, the number of drives and the type of array chosen should be done together not drives purchased then use determined based on that arbitrary number, but two drive chassis are so common that it is worth mentioning as a case.

Likewise, with a four drive array the only real choice to consider is RAID 10.  There is no need for further evaluation.  Simply select RAID 10 and continue.

An awkward case is a three drive array.  It is very, very rare that we are limited to three drives as the only common chassis limited to three drives was the Apple Xserve and this has been off of the market for some time so the need to deal with decision making around three spindle arrays should be extremely unlikely.  In cases where we have three drives it is often best to seek guidance but the most common approaches are to add a fourth drive and ergo chose RAID 10 or, if capacity of greater than a single drive’s worth is not needed, to put all three drives into a single triple-mirror RAID 1.

For all other cases, therefore, we are dealing with five to twenty five drives.  Since we have eliminated the situations where RAID 0 and RAID 1 would apply we are left with all common scenarios coming down to RAID 6 and RAID 10, and these constitute the vast majority of cases.  Choosing between RAID 6 and RAID 10 becomes the biggest challenge that we will face as we must look solely at a our “soft” needs of reliability, performance and capacity.

Choosing between RAID 6 and RAID 10 should not be incredibly difficult.  RAID 10 is ideal for situations where performance and safety are the priorities.  RAID 10 has much faster write performance and is safe regardless of disk type used (low cost consumer disks can still be extremely safe, even in large arrays.)  RAID 10 scales well to extremely large sizes, much larger than should be implemented using rules of thumb!  RAID 10 is the safest of all choices, it is fast and safe.  The obvious downsides are that RAID 10 has less storage capacity from the same disks and is more costly on the basis of capacity. It must be mentioned that RAID 10 can only utilize an even number of disks, disks are added in pairs.

RAID 6 is generally safe and fast but never as safe or as fast as RAID 10.  RAID 6 specifically suffers from write performance so is very poorly suited for workloads such as databases and heavily mixed loads like in large virtualization systems.  RAID 6 is cost effective and provides a heavy focus on available capacity compared to RAID 10.  When budgets are tight or capacity needs dominate over performance RAID 6 is an ideal choice.  Rarely is the difference in safety between RAID 10 and RAID 6 a concern except in very large systems with consumer class drives.  RAID 6 is subject to additional risk with consumer class drives that RAID 10 is not affected by which could warrant some concern around reliability in larger RAID 6 systems such as those above roughly 40TB when consumer drives are used.

In the small business space especially, the majority of systems will use RAID 10 simply because arrays rarely need to be larger than four drives.  When arrays are larger RAID 6 is the more common choice due to somewhat tight budgets and generally low concern around performance.  Both RAID 6 and RAID 10 are safe and effective solutions for nearly all usage scenarios with RAID 10 dominating when performance or extreme reliability are key and RAID 6 dominating when cost and capacity are key.  And, of course, when storage needs are highly unique or very large, such as larger than twenty five spindles in an array, remember to leverage a storage consultant as the scenario can easily become very complex.  Storage is one place where it pays to be extra diligent as so many things depend upon it, mistakes are so easy to make and the flexibility to change it after the fact is so low.

Practical RAID Performance

Choosing a RAID level is an exercise in balancing many factors including cost, reliability, capacity and, of course, performance.  RAID performance can be difficult to understand especially as different RAID levels use different techniques and behave rather differently from each other in some cases.  In this article I want to explore the common RAID levels of RAID 0, 5, 6 and 10 to see how performance differs between them.

For the purposes of this article, RAID 1 will be assumed to be a subset of RAID 10.   This is often a handy way to think of RAID 1 – as simply being a RAID 10 array with only a single mirrored pair member.  As RAID 1 is truly a single pair RAID 10 and behaves as such this works wonderfully for making RAID performance easy to understand as it simply maps into the RAID 10 performance curve.

There are two types of performance to look at with all storage: reading and writing.  In terms of RAID reading is extremely easy and writing is rather complex.  Read performance is effectively stable across all RAID types.  Writing, however, is not.

To make discussing performance easier we need to define a few terms as we will be working with some equations. In our discussions we will use N to represent the total number of drives, often referred to as spindles, in our array and we will use X to refer to the performance of each drive individually.  This allows us to talk in terms of relative performance as a factor of the drive performance allowing us to abstract away the RAID array and not have to think in terms of raw IOPS.  This is important as IOPS are often very hard to define but we can compare performance in a meaningful way by speaking to it in relationship to the individual drives within the array.

It is also important to remember that we are only talking about the performance of the RAID array itself, not an entire storage subsystem.  Artifacts such as memory caches and solid state caches will do amazing things to alter the overall performance of a storage subsystem, but do not fundamentally change the performance of the RAID array itself under the hood.  There is no simple formula for determining how different cache options will impact the overall performance but suffice it to say that it can be very dramatic but this depends heavily not only on the cache choices themselves but also heavily upon workload. Even the biggest, fastest, most robust cache options cannot change the long term, sustained performance of an array.

RAID is complex and many factors influence the final performance.  One is the implementation of the RAID system itself.  A poor implementation might cause latency or may fail to take advantage of the available spindles (such as having a RAID 1 array read only from a single disk instead of from both simultaneously!)  There is no easy way to account for deficiencies in specific RAID implementations so we must assume that all are working to the limits of the specification as, indeed, any enterprise RAID system will do. It is primarily hobby and consumer RAID systems that fail to do this.

Some types of RAID also have dramatic amounts of computational overhead associated with them while others do not.  Primarily parity RAID levels require heavy processing in order to handle write operations with different levels having different amounts of computation necessary for each operation.  This introduces latency, but does not curtail throughput.  This latency will vary, however, based on the implementation of the RAID level as well as on the processing capability of the system in question.  Hardware RAID will use something like a general purpose CPU (often a Power or ARM RISC processor) or a custom ASIC to handle this while software RAID hands this off to the server’s own CPU.  Often the server CPU is actually faster here but consumes system resources.  ASICs can be very fast but are expensive to produce.  This latency impacts storage performance but is very difficult to predict and can vary from nominal to dramatic.  So I will mention the relative latency impact with each RAID level but will not attempt to measure it.  In most RAID performance calculations, this latency is ignored but it is important to understand that it is present and could, depending on the configuration of the array, have a noticeable impact on a workload.

There is, it should be mentioned, a tiny performance impact to read operations due to efficiencies in the layout of data on the disk itself.  Parity RAID requires there to be data on the disks that is useless during a healthy read operation but cannot be used to speed it up.  The actually results in it being slightly slower.  But this impact is ridiculously small and is normally not measured and so can be ignored.

Factors such as stripe size also impact performance, of course, but as that is configurable and not an intrinsic artifact in any RAID level I will ignore it here.  It is not a factor when choosing a RAID level itself but only in configuring one once chosen.

The final factor that I want to mention is the read to write ratio of storage operations.  Some RAID arrays will be used almost purely for read operations, some almost solely for write operations but most use a blend of the two, likely something like eighty percent read and twenty percent write.  This ratio is very important in understanding the performance that you will get from your specific RAID array and understanding how each RAID level will impact you.  I refer to this as the read/write blend.

We measure storage performance primarily in IOPS.  IOPS stands for Input/Output Operations Per Second (yes, I know that the letters don’t line up well, it is what it is.)  I further use the terms RIOPS for Read IOPS, WIOPS for Write IOPS and BIOPS for Blended IOPS which would come with a ration 80/20 or whatever.  Many people talk about storage performance with a single IOPS number.  When this is done they normally mean Blended IOPS at 50/50.  However, rarely does any workload run at 50/50 so that number can be extremely misleading.  Two numbers, RIOPS and WIOPS is what is needed to understand performance and these two together can be used to find any IOPS Blend that is needed.   For example, a 50/50 blend is as simple as (RIOPS * .5) + (WIOPS * .5).  The more common 80/20 blend would be (RIOPS * .8) + (WIOPS * .2).

Now that we have established some criteria and background understanding we will delve into our RAID levels themselves and see how performance varies across them.

For all RAID levels, the Read IOPS number is calculated using NX.  This does not address the nominal overhead numbers that I mention above, of course.  This is a “best case” number but the real world number is so close that it is very practical to simply use this formula.  Since take the number of spindles (N) and multiple by the IOPS performance of an individual drive (X).  Keep in mind that drives often have different read and write performance so be sure to use the drives Read IOPS rating or tested speed for the Read IOPS calculation and the Write IOPS rate or tested speed for the Write IOPS calculation.


RAID 0 is the easiest RAID level to understand because there is effectively no overhead to worry about, no resources consumed to power it and both read and write get the full benefit of every spindle, all of the time.  So for RAID 0 our formula for write performance is very simple: NX.  RAID 0 is always the most performant RAID level.

An example would be an eight spindle RAID 0 array.  If an individual drive in the array delivers 125 IOPS then our calculation would be from N = 8 and X = 125 so 8 * 125 yielding 1,000 IOPS.  Since both read and write IOPS are the same here, it is extremely simple as we get 1K RIOPS, 1K WIOPS and 1K with any blending thereof.  Very simple.  If we didn’t know the absolute IOPS of an individual spindle we could refer to an eight spindle RAID 0 as delivering 8X Blended IOPS.


RAID 10 has the second simplest RAID level to calculate.  Because RAID 10 is a RAID 0 stripe of mirror sets, we have no overhead to worry about from the stripe but each mirror has to write the same data twice in order to create the mirroring.  This cuts our write performance in half compared to a RAID 0 array of the same number of drives.  Giving us a write performance formula of simply: NX/2  or .5NX.

It should be noted that at the same capacity, rather than the same number of spindles, RAID 10 has the same write performance as RAID 0 but double the read performance – simply because it requires twice as many spindles to match the same capacity.

So an eight spindle RAID 10 array would be N = 8 and X = 125 and our resulting calculation comes out to be (8 * 125)/2 which is 500 WIOPS or 4X WIOPS.  A 50/50 blend would result in 750 Blended IOPS (1,000 Read IOPS and 500 Write IOPS.)

This formula applies to RAID 1, RAID 10, RAID 100 and RAID 01 equally.

Uncommon options such as triple mirroring in RAID 10 would alter this write penalty.  RAID 10 with triple mirroring would be NX/3, for example.


While RAID 5 is deprecated and should never be used in new arrays I include it here because it is a well known and commonly used RAID level and its performance needs to be understood.  RAID 5 is the most basic of the modern parity RAID levels.  RAID 2, 3 & 4 are no longer found in production systems and so we will not look into their performance here.  RAID 5, while not recommended for use today, is the foundation of other modern parity RAID levels so is important to understand.

Parity RAID adds a somewhat complicated need to verify and re-write parity with every write that goes to disk.  This means that a RAID 5 array will have to read the data, read the parity, write the data and finally write the parity.  Four operations for each effective one.  This gives us a write penalty on RAID 5 of four.  So the formula for RAID 5 write performance is NX/4.

So following the eight spindle example where the write IOPS of an individual spindle is 125 we would get the following calculation: (8 * 125)/4 or 2X Write IOPS which comes to 250 WIOPS.  In a 50/50 blend this would result in 625 Blended IOPS.


RAID 6, after RAID 10, is probably the most common and useful RAID level in use today.  RAID 6, however, is based off of RAID 5 and has another level of parity.  This makes it dramatically safer than RAID 5, which is very important, but also imposes a dramatic write penalty as each write operation requires the disks to read the data, read the first parity, read the second parity, write the data, write the first parity and then finally write the second parity.  This comes out to be a six times write penalty, which is pretty dramatic.  So our formula is NX/6.

Continuing our example we get (8 * 125)/6 which comes out to ~167 Write IOPS or 1.33X.  In our 50/50 blend example this is a performance of  583.5 Blended IOPS.  As you can see, parity writes cause a very rapid decrease in write performance and a noticeable drop in blended performance.

RAID 7 (aka RAID 5.3 or RAID 7.3)

RAID 7 is a somewhat non-standard RAID level with triple parity based off of the existing single parity of RAID 5 and the existing double parity of RAID 6.  The only current implementation of RAID 7 is ZFS’ RAIDZ3.  Because RAID 7 contains all of the overhead of both RAID 5 and RAID 6 plus the additional overhead of the third parity component we have a write penalty of a staggering eight times.  So our formula for finding RAID 7 write performance is NX/8.

In our example this would mean that (8 * 125)/8 would come out to 125 Write IOPS or 1X.  So with eight drives in our array we would get only the write performance of a single, stand alone drive.  That is significant overhead.  Our blended 50/50 IOPS would come out to only 562.5.

Complex RAID

Complex RAID levels or Nested RAID levels such as RAID 50, 60, 61, 16, etc. can be found using the information above and breaking the RAID down into its components and applying each using the formulæ provided above.  There is no simple formula for these levels because they have varying configurations.  It is necessary to break them down into their components and apply the formulæ multiple times.

RAID 60 with twelve drives, two sets of six drives, where each drive is 150 IOPS would be done with two RAID 6s.  It would be the NX of RAID 0 where N is two (for two RAID 6 arrays) and the X is the resultant performance of each RAID 6.   Each RAID 6 set would be (6 * 150)/6.  So the full array would be 2((6 * 150)/6).  Which results in 300 Write IOPS.

The same example as above but configured as RAID 61, a mirrored pair of RAID 6 arrays, would be the same performance per RAID 6 array, but applied to the RAID 1 formula which is NX/2 (where X is the resultant performance of the each RAID array.)  So the final formula would be 2((6 * 150)/6)/2 coming to 150 Write IOPS from twelve drives.

Performance as a Factor of Capacity

When we are producing RAID performance formulæ we think of these in terms of the number of spindles which is incredibly sensible.  This is very useful in determining the performance of a proposed array or even an existing one where measurement is not possible and allows us to compare the relative performance between different proposed options.  It is in these terms that we universally think of RAID performance.

This is not always a good approach, however, because typically we look at RAID as a factor of capacity rather than of performance or spindle count.  It would be very rare, but certainly possible, that someone would consider an eight drive RAID 6 array versus an eight drive RAID 10 array.  Once in a while this will occur due to a chassis limitation or some other, similar reason.  But typically RAID arrays are viewed from the standpoint of total array capacity (e.g. usable capacity) rather than spindle count, performance or any other factor.  It is odd, therefore, that we should then switch to viewing RAID performance as a function of spindle count.

If we change our viewpoint and pivot upon capacity as the common factor, while still assuming that individual drive capacity and performance (X) remains constant between comparators then we arrive at a completely different landscape of performance.  In doing this we see, for example, that RAID 0 is no longer the most performant RAID level and that read performance varies dramatically instead of being a constant.

Capacity is a fickle thing but we can distill it out to the number of spindles necessary to reach desired capacity.  This makes this discussion far easier.  So our first step is to determine our spindle count needed for raw capacity.  If we need a capacity of 10TB and are using 1TB drives, we would need ten spindles, for example.  Or if we need 3.2TB and are using 600GB drives we would need six spindles.  We will, different than before, refer to our spindle count as R.  As before, performance of the individual drive is represented as X.  (R is used here to denote that this is the Raw Capacity Count, rather that the total Number of spindles.)

RAID 0 remains simple, performance is still RX as there are no additional drives.  Both read and write IOPS are simply NX.

RAID 10 has RX Write IOPS but 2RX Read IOPS.  This is dramatic.  Suddenly when viewing performance as a factor of stable capacity we find that RAID 10 has double read performance over RAID 0!

RAID 5 gets slightly trickier.  Write IOPS would be expressed as ((R + 1) * X)/4.  The Read IOPS are expressed as ((R +1) * X).

RAID 6, as we expect, follows the pattern that RAID 5 projects.  Write IOPS for RAID 6 are ((R + 2) * X)/6.  And the Read IOPS are expressed as ((R + 2) * X).

RAID 7 falls right in line.  RAID 7 Write IOPS would be ((R + 3) * X)/8.  And the Read IOPS are ((R + 3) * X).

This vantage point changes the way that we think about performance and, when looking purely at read performance, RAID 0 becomes the slowest RAID level rather than the fastest and RAID 10 becomes the fastest for both read and write no matter what the values are for R and X!

If we take a real world example of 10 2TB drives to achieve 20TB of usable capacity with each drive having 100 IOPS of performance and assume a 50/50 blend, the resultant IOPS would be:  RAID 0 with 1,000 Blended IOPS, RAID 10 with 1,500 Blended IOPS (2,000 RIOPS / 1,000 WIOPS), RAID 5 with 687.5 Blended IOPS (1,100 RIOPS / 275 WIOPS), RAID 6 with 700 Blended IOPS (1,200 RIOPS / 200 WIOPS) and finally RAID 7 with 731.25 Blended IOPS (1,300 RIOPS / 162.5 WIOPS.)  RAID 10 is a dramatic winner here.

Latency and System Impact with Software RAID

As I have stated earlier, RAID 0 and RAID 10 have, effectively, no system overhead to consider.  The mirroring operation requires essentially no computational effort and is, for all intents and purposes, immeasurably small.  Parity RAID does have computational overhead and this results in latency at the storage layer and system resources being consumed.  Of course, if we are using hardware RAID those resources are dedicated to the RAID array and have no function but to be consumed in this role.  If we are using software RAID, however, these are general purpose system resources (primarily CPU) that are consumed for the purposes of the RAID array processing.

The impact to even a very small system with a large amount of RAID is still very small but it can be measured and should be considered, if only lightly.  Latency and system impact are directly related to one another.

There is no simple way to state latency and system impact for different RAID levels except in this way: RAID 0 and RAID 10 have effectively no latency or impact, RAID 5 has some latency and impact, RAID 6 has roughly twice as much computational latency and impact as RAID 5 and RAID 7 has roughly triple the computational latency and impact as RAID 5.

In many cases this latency and system impact will be so small that they cannot be measured with standard system tools and as modern processors become increasingly powerful the latency and system impact will continue to diminish.  Impact has been considered negligible for RAID 5 and RAID 6 systems on even low end, commodity hardware since approximately 2001.  But it is possible on heavily loaded systems with a large amount of parity RAID activity that there could be contention between the RAID subsystem and other processes requiring system resources.

Reference: The IT Hollow – Understanding the RAID Penalty

Article originally posted to the StorageCraft Blog – RAID Performance.