Let’s say you have 2 different applications, A and B, and only have one physical server. What is a best way to share that server between these 2 applications? You have several options:

 

• Create different databases on the same SQL Server instance
• Install 2 separate instances of SQL Server on the same physical computer
• Install 2 VMware machines

 

As you may have learned from one of my previous articles, VMware and SQL Server do not mix; so it shouldn’t even be considered.

 

So you’re left with 2 choices: 2 separate databases or 2 different instances. But which is better?

 

In some cases, you may not have a choice but to install 2 different instances. The following are some reasons why you might want to follow this approach:

 

• Applications have hard-coded and common database names. For example, if both applications needed to create a database named Customers. A good example of such an application is BizTalk which, by the way, I believe that this is not the right way to do it – in many projects, different databases play roles of ‘namespaces’. But, at first, namespaces are introduced in MS SQL 2005, but even on SQL 2000 using databases as namespaces should be considered as a bad practice.
• The second reason why you might need to install separate instances is because of different requirements in server-wide settings. If they are not compatible, then you have no choice. These settings may include:
• Server default collation
• Security settings
• Logins
• Linked servers
• And any other objects in the ‘server’ namespace.

 

Fortunately, in many cases, an ordinary application just follows the connection string you provide: login, server name, databases. So you can create any number of databases on your server and share it between such applications. It’s true that in 90% of cases, simple applications do not create logins, do not reboot the server, do not drop or create databases. So, using separate databases provides them safe sandboxes, right? Let’s verify.

 

First I create 2 databases, A and B, on one instance of SQL server (2000). Please set recovery model to Simple, and pre-allocate 100Mb for data and 50Mb for log.

 

 

 

Then, set the instance’s memory fixed at 70Mb:

 

 

Of course, it is a ridiculously small amount of memory for a production server; but we are making a small-scale experiment. Instead of 70MB, think about 8GB, and instead of 90MB tables, we’re going to create them using the following script:

 

create table Docs (n int identity, k int not null, v varchar(128))

create table Big (n int identity, k int not null, v varchar(128))

GO

insert into Docs (k,v) select 1, 'this is a test'

GO

declare @t datetime, @n int

set @t=getdate()

set @n=18

while @n>0 begin

  insert into Docs (k,v) select k+n,v from Docs

  set @n=@n-1

end

GO

create clustered index PP on Big (n)

GO

declare @n int

set @n=8

while @n>0 begin

  insert into Big (k,v) select k,v from Docs

  set @n=@n-1

  end

GO

checkpoint

 

Think about huge tables. What is real here is that a table size (90MB, >2M rows) is bigger, than the server memory (70MB). That script must be executed on both databases: A and B.

 

Now, we can perform a full table scan from both databases. Execute the following scripts several times:

 

-- Scan A

declare @t datetime set @t=getdate()

select max(v) from A..Big

select datediff(ms,@t,getdate())

 

-- Scan B

declare @t datetime set @t=getdate()

select max(v) from B..Big

select datediff(ms,@t,getdate())

 

Ignore the duration of the first executions; we are interested in last:

 

• ScanA  9693 6050 4896  
• ScanB  2913 2933 2903

 

For some reason, database B works much faster than database A. I don’t have a good explanation; I guess it’s because of the fragmentation of the disk or maybe it’s created on different sectors of the disk.

 

Anyway, both scans represent some heavy read activity, usual for the OLAP/Reporting system. Now for an OLTP test, we randomly read 1000 records from different places:

 

-- Random A

declare @t datetime set @t=getdate()

declare @k bigint, @n int, @v varchar(128)

set @n=1000

set @k=1

while @n>0 begin

  set @k=@k+77777

  select @v=v from A..Big where n=@k%2000000

  set @n=@n-1

  end

select datediff(ms,@t,getdate())

GO

 

 

Make sure you clear the SQL Server cache before execution, using:

 

DBCC DROPCLEANBUFFERS

 

The first execution time was 9193ms, while the second execution time was only 20ms! It reminds us about two facts, well known before but are easily overseen today, because their effects are more and more masked by RAIDs and powerful disk arrays, making them less evident. However, these facts remain to be true:

 

Fact 1: A hard drive is not a random access device (for databases). As you see, it took the same time (9 seconds for the ‘cold’ server) to read 2’000’000 records using a sequential read (table scan) and to read 1000 records in random order. Sequential read was 2000 times faster!

 

* This is one of the reasons, why object-oriented databases (even when they are more logical and closer to the commonly-accepted OO ideology) could not win over relational databases. OO databases processed data object by object, generating random read patterns, and could not compete with relational ones

 

Fact 2: A ‘cold’ execution (SQL Server has been just started, or is accessing data for the very first time) can be more than 450 times (9193/20) slower, than subsequent executions, when data is cached.

 

* That reminds me something that I experienced. In one company, timeout for the IIS .Net applications was 30 seconds (default). Because of the effect mentioned above, the execution time of some complicated queries, which normally took 1-2 seconds to execute, took 40-50 seconds (on a ‘cold’ server) which caused a timeout error.

 

Of course, testers did not know it. So, every time QA server had been rebooted, I had 5-10 reopened issues in bug tracker about timeouts. Everything was ok the second time. Interestingly, many people could not believe that execution time can even vary by as much as two times, so I had to make a small demo to prove it.

 

Is it applicable for the modern, powerful disk arrays and RAID controllers with a big cache? Yes, but in such configurations DBCC DROPCLEANBUFFERS is not enough – it flushes the cache of SQL Server, but not the controllers’. On a powerful production system, I had the following results:

 

• ‘Cold’ SQL Server, ‘cold’ controller – 800ms
• ‘Cold’ SQL Server, ‘hot’ controller – 280ms
• ‘Hot’ SQL server (no access to controller, everything is in cache) – 11ms

 

But let’s return to our main subject. Our query on database A is ‘hot’. But then as time passes, there is activity in the other database, and the data in cache is gone:

 

So we run script Random A (RA) several times, and get the same execution time – 20ms. Then we run Scan on database B (SB):

 

RA=20, RA=20, SB=2983, RA=20 – no effect!

 

But when we do it twice or more times:

 

RA=20, RA=20, SB= 2863, SB=3086, RA=7963 (!!!)

 

SQL Server 2005 has another caching strategy, and the same effect is much more difficult to reproduce.

 

On the contrary, nothing like this happens when you use 2 instances. With 2 instances (each having a half of a memory, 35Mb) RA execution time is always 20ms, no matter how many scans are executed on another instance. However, with less memory (less caching and worse cache hits ratio), the Scan time degrades. For Scan A, it degraded from about 4200 ms to 7600 ms.

 

So, when multiple databases share the same server, high activity in one of them rebalances the SQL Server cache so the most active database benefits from it, while the less active can suffer from lack of resources – similar to a “DOS” attack.

 

So, should we install 2 instances instead? Is it the solution? There are many cons for having 2 instances:

• You should still consider ‘cold server’ issues, because it’s not an excuse for the customers who get timeouts.
• If you use 2 instances with statically-allocated memory, you are not using server resources efficiently. If you allow a dynamic memory configuration, then you get the same “re-balancing” problems, but in a much worse form.
• If both instances are accessing the same RAID/external disk array, they compete for the same controller cache memory anyway, with the same time of “balancing” issues, not inside SQL Server, but in the controller.
• Finally, SQL 2005 handles such balancing issues more efficiently than SQL Server 2000.

 

So, unless you have some fatal issues that do not allow you to put everything on the same server, the best thing to do is to use the rule of “Occam’s razor” - entities should not be multiplied beyond necessity.