This delivery guide provides a primer for solution implementers who are starting a project which will (or may) use Windows Azure SQL Database. The guide is aimed at experienced architects and developers who already have a background with SQL Server and perhaps
with the .NET Framework. A good familiarity with T-SQL, SQL Server features and administration, and application architectures based on the Microsoft stack is assumed. The guide familiarizes the reader with the things they need to know to get started designing
and delivering solutions which include the SQL Database data platform.
The path to an effective SQL Database solution begins with solid planning. Early architectural decisions will affect the rest of the project and the ultimate success of the solution. Planning the data platform for your scenario involves several key decisions,
starting with whether SQL Database or on-premise SQL Server is the best tool for the job. Assuming SQL Database will play a role in your solution, there are a variety of potential application architectures to choose from. Certain factors to be understood are
the SQL Database Service Level Agreement (SLA), the impact of latency in the chosen architecture, availability and disaster recovery scenarios, and developer tools.
This section dives into these topics to help you make the appropriate decisions early-on.
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If you are developing a solution which will include one or more SQL Server relational databases, the first architectural/planning decision that must be made is whether to deploy that database to SQL Database in the cloud or to an on-premise SQL Server instance.
SQL Database offers an extremely easy-to-use relational database engine which is architected natively as a large-scale, highly available, multi-tenant cloud service.
There is an economic and operational argument for eliminating onsite hardware and software and all the upkeep that goes with it. And extending the reach of the database and possibly other application components outside the enterprise firewall can enable
many new scenarios.
How to decide for SQL Database, when sometimes on-premise SQL Server appears to be the more appropriate choice? There are differences in the breadth of functionality provided by the two products. There are different capacity constraints, and some features
behave differently between SQL Database and traditional on-premise SQL Server. At the end of the day, the most important consideration is what will lead to a successful solution and a satisfied customer? The choice between SQL Database and on-premise SQL Server
should be made with this as the fundamental criterion.
The decision tree in Figure 1 illustrates some of the factors that should go into making the choice between SQL Database and on-premise SQL Server.
Figure 1 - Choosing Between SQL Database and On-Premise SQL Server
As Figure 1 shows, there are several decision points (technical, economic, and policy-related) which may lead you one way or the other.
It is worth noting that requirements for unstructured storage are not considered a deciding factor between the two options. With on-premise SQL Server, you have SQL’s binary and large text data types available, as well as FILESTREAM storage and all the resources
available from the Windows operating system (file system, MSMQ, etc.). With SQL Database, SQL’s binary and large text data types are also available, although FILESTREAM storage is not supported. Windows Azure tables, blobs and queues round out the support
for unstructured storage. So, a combination of structured and unstructured storage needs can most likely be met equally well on-premise or on the Azure platform.
Once decided that SQL Database is the right choice for your solution, you will also need to choose the edition (Web or Business), the database size (various choices between 1GB and 150GB) and the geographic location(s) at which the database(s) are hosted.
(Because this guide is focused on SQL Database rather than on-premise SQL Server, no further detail is provided here about the on-premise path.)
Figure 2 provides a decision path through the edition and size options for SQL Database between the Web and Business Editions of SQL Database.
Figure 2 - SQL Database Choices
The geographic location depends on where your users are, to what degree you want to exploit geographic distribution for disaster tolerance, and what regulatory/compliance factors, if any, apply to your situation.
The following table lists the SQL Database hosting locations at the time of this writing. There is no important technical difference between the data centers, other than their location. Note that bandwidth from the Asia data centers is currently priced higher
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A key factor in making the data platform decision is compliance with relevant regulations or laws related to data handling. Depending on the data involved and the country, or other jurisdiction, there may be limitations on where and how data can be stored.
This step from the decision tree in Figure 1 (“Can SQL Database satisfies compliance requirements?”) is expanded into greater detail in Figure 3.
Figure 3 - Evaluating Compliance Factors Related to SQL Database vs. On-Premise Data Hosting
The decision tree in Figure 1 also calls out security as a consideration affecting the decision to use SQL Database. The term “security” is used here in a strictly technical sense, to differentiate it from the issues related to compliance. At the technical
level, there are many security features of SQL Server that are fully supported (or even mandatory, such as SSL connection encryption) in SQL Database and some which are not available.
Considering the scope of a single database, most of the security features of SQL Server are available in SQL Database. These include user and role definition and access control via GRANT/ DENY/REVOKE on objects with the database. At the server level, SQL
Database allows logins to be created (with SQL Server authentication only) and provides a set of server-level roles similar to those in on-premise SQL Server.
Connections to SQL Database are SSL-encrypted by default – this cannot be disabled. And, all connectivity to SQL Database is protected by a firewall. You must create firewall rules to allow access from the location(s) where client code resides.
There are, however, some security features of on-premise SQL Server which do not apply to SQL Database. These include:
SQL Databases are not encrypted on disk in the Azure data center.
As part of data platform selection, you should ensure that the chosen platform meets the specific security-related requirements for your solution.
In broad terms, based on preliminary data, ROI analysis leans in favor of SQL Database in the following conditions:
ROI analysis has often favored on-premise SQL Server in the following conditions:
As a tool in the solution architect’s toolbox, SQL Database is useful in a variety of scenarios. This section presents several common architectural patterns used by SQL Database early adopters.
As might be expected, SQL Database is a natural and highly effective choice when a Windows Azure application requires a relational data store. When SQL Database and the other Windows Azure components are deployed to the same site, code-to-database latency
is essentially eliminated. Also, bandwidth in and out of SQL Database is free when the client endpoint is within the same data center as Azure application.
A typical Windows Azure architecture, using Web and Worker roles with one or more SQL Databases, is depicted in Figure 4.
Figure 4 - Typical Windows Azure Architecture
With the recent support in Windows Azure for full IIS in web roles and custom VMs, such architecture can also include almost any other kind of presentation and business tier application code. For example, if a customer has a large legacy COM+ layer fronted
by ASP.NET web pages and upgrading this code is not an option, they might still be able to deploy the application tier to Windows Azure as custom VMs, with SQL connection strings pointing to one or more SQL Databases. Such a case is depicted in Figure 5. Of
course, this is just one simple example - the possibilities with custom VMs are very broad.
Figure 5 - Azure Custom VM's Hosting COM+ and ASP.NET Code, Hitting SQL Database
Example Customer Scenarios
Another great use for SQL Database is as a relational store in a “spanning application”. A spanning application, sometimes also called a hybrid application, is a solution in which some components run on-premise and some run in the cloud.
A spanning architecture can be useful for bringing together the attributes of SQL Database with the attributes of internally hosted custom code. For example, using SQL Database as a data platform can provide the benefits of high availability and a management-free
hosting experience, eliminating the headaches and cost associated with running an on-premise database server. All too often, attempting to run a production database server without the proper infrastructure simply results in a poor service level to the business.
Properly architected SQL Database can mitigate this.
SQL Database can also provide a data store accessible from locations dispersed across geographies and organizational boundaries, with a fraction of the effort and cost that might be required to deliver the same experience in more traditional ways.
A spanning architecture, in addition, can leave complete flexibility on how other layers of the application stack are assembled. Does the application use an assemblage of Office, Sharepoint, or other components not suited to external cloud hosting? No problem.
Does the application integrate a mish-mash of multi-vendor technologies, yet need a relational SQL data store as a back end? No problem. Do application tier instances need to run on separate networks, with separate authentication methods and user directories,
while connecting to the same database with a trusted sub-system model? No problem. Does the application tier require some specialized hardware or licensing accommodation, preferably combined with a standard, cost-effective, and easily managed RDBMS? In all
these cases, a spanning application can be an effective approach.
A simpler and sometimes valuable way for SQL Database to extend the reach of an on-premise application is when acting as an extension of an on-premise solution. This differs from a spanning application in that the on-premise application is fully self-sufficient.
However, it is able to provide some incremental functionality through an extension into the cloud; the cloud then hosts a “spoke” supported by the on-premise “hub”.
One example of this approach is a SQL Database used to expose partial data from an on-premise Line-of-Business (LOB) application to roaming users. For example, a frequently updated product and price list could be hosted in a SQL Database, regularly synchronized
from an on-premise solution. This product/price list could then be accessed by roaming users from their laptops or mobile devices, most likely in combination with some desktop tool or with other Azure-hosted code. In fact, it would be easy for the users of
this data to include employees of partner or customer companies, as well.
Figure 6 - Extension of Partial/Full On-Premise Data Set to External Users
Much of the same objective can be achieved with VPN and/or DMZ-hosted servers. However, there is cost and work associated with setting this infrastructure up, properly securing it, and maintaining it. By comparison, deploying the data to a SQL Database is
simpler in terms of effort and cost.
One of the key value propositions for cloud computing is the ability to scale up and scale down promptly and cost-effectively. Some business solutions naturally have large spikes in processing load or volume. Examples include:
SQL Database is a great tool for supporting capacity bursts at the data tier. Databases can be created and dropped with ease. The SQL Database architecture causes databases within a single service (i.e. logical SQL Database server) to be spread across a
large pool of computing resources, so the “server” will not risk be overtaxed. And, SQL Database usage charges accrue day-by-day, so adding and removing databases within narrow time windows results in granular, cost-effective billing.
Figure 7 depicts a notional Windows Azure architecture in which the data tier scales up and then down in response to some business-related surge in activity.
Figure 7 - Before, During, and After a SQL Database Capacity Burst
Although SQL Database provides the tools to easily support capacity bursting, some design forethought is required to allow the application to spread data across the available SQL Databases. The typical pattern for doing this involves consciously splitting
data across multiple databases and ensuring the application know which connection string to use to get the information it needs. Usually it is best to split the data across databases horizontally, a technique sometimes called “sharding”.
In the sharding approach, the ‘big’ or heavily accessed tables are logically partitioned across databases. For example, in a customer-centric solution, 10% of the customers may be stored in each of 10 identically structured databases along with all their
related data in other tables. Common data may be in a separate database or may be duplicated in each database.
The client code must have the awareness to connect to the proper database for the customer relevant to the current data access request. There will be more discussion of sharding, and other scale-out approaches, later in this document.
SQL Database will also be introducing a new feature called Federations to help with scale-out implementations. This will most likely become available in 2011. Previews of this feature have been shown at PDC and other technical conferences. More on Federations
will also be covered later in this document.
Before deciding to run a solution partially or entirely on the SQL Database data platform, it is important to understand the
Service Level Agreement (SLA) extended by Microsoft.This SLA is an integral part of the service. When you, or your customer, buy SQL Database, you are buying the service level defined in this document.
The SLA for SQL Database is an availability SLA. It promises a specific uptime percentage. If the service fails to meet that uptime percentage in a given month, the affected customers are entitled to a partial refund of the fees for that month.
SQL Database does not currently provide any SLA for performance or for security. The most current SLA document can be found
Currently, the availability SLA for SQL Database is 99.9% uptime in a given month. A 10% refund is granted if availability falls below 99.9% and a 25% refund is granted if availability falls below 99%. Note that the SLA allows for up to 10 hours of
scheduled downtime per calendar year, which is excluded from the availability calculation. Customers will be notified of scheduled downtime at least five days in advance.
In selecting SQL Database as a data platform, and in planning the operational details of your solution, it is important to be cognizant of this SLA, what it covers, and what it does not cover. A small number of customers need a better uptime assurance than
this. On the other hand, many, many customers would be very happy to achieve three nines of availability for what SQL Database costs.
SQL Database has a high-availability (HA) architecture built-in, it actually exposes nothing to administrators in terms of HA configuration. HA concepts from on-premise SQL Server, such as failover clustering, database mirroring, and log shipping, do not
apply in SQL Database. However, SQL Database’s internal storage architecture is such that all writes are triply redundant across independent commodity servers. So, a high level of data protection is inherently provided.
The triple redundancy within the Azure data center combined with the 99.9% availability SLA essentially is the SQL Database HA story. There are no other features or ‘knobs’ exposed.
This leaves open the question of disaster recovery – how does one protect against the unlikely scenario of an entire Azure data center being unavailable or lost? There is no provision for remote replication built directly into SQL Database. There is, however,
an offering which allows partial or full synchronization across SQL Database sites or between SQL Database and an on-premise SQL Server instance. This is discussed later in this document in the section on “SQL Data Sync.”
SQL Database is a relational database engine made specifically for the cloud. As such, it is able to deliver on many of the promises of cloud computing which relate to simpler and cost effective management. In the planning stages of a project which will
use SQL Database, some categories of operations and infrastructure planning can essentially be skipped.
A partial list of the issues that are mitigated by SQL Database:
Although SQL Database mitigates a broad swath of issues that go along with running on-premise database servers, today, it does not cover the full breadth of features in on-premise SQL Server. First, it should be noted that SQL Database is roughly equivalent
to the Database Engine in SQL Server. Other components of SQL Server – namely Analysis Services and Integration Services – are not provided by SQL Database. A Windows Azure-based Reporting Services offering was announced in late 2010; that offering is not
included in this guide.
Within the Database Engine, the following are unsupported by SQL Database:
It is important to note that SQL Database is a constantly changing product and new features are continuously being rolled out. For latest information on feature differences, see the SQL Database documentation, especially
Guidelines and Limitations and the
Support for SQL Database has been included in most of the latest-generation development tools from Microsoft. The following tools are recommended for working with SQL Database.
In most respects, building relational SQL databases for SQL Database is essentially identical to building them in on-premise SQL Server. As with any tool, however, there are certain unique factors which come in to play when developing for SQL Database.
This section covers many of those topics to prepare you for effective development. Most of concepts about SQL Server development will apply to SQL Database and this guide won’t revisit them. Certain things that are different, or where you may need to make
different decisions, are covered in this section.
In broad terms, the design of a data model for SQL Database is no different than it would be for an on-premise SQL Server deployment. There are some lower-level technical details which differ, but they don’t change the essentials of how a data model is built.
That said this section enumerates some of the technical details to be aware of in designing your SQL Databases.
All tables must have a clustered index. In on-premise SQL Server, tables may be created without clustered indexes (such tables are referred to as heaps). For internal reasons related to SQL Database’s redundant/replicated storage, heaps
are not allowed. A CREATE TABLE statement that does not specify a clustered index can be executed, but an error will be thrown if an INSERT is attempted before a clustered index is added to the table.
No filegroup may be specified for tables or indexes. This is a simple consequence of the fact that SQL Database eliminates physical management of database files. When a table is created, SQL Database manages where it goes, as well as where/how
database files are laid out on disk.
Table partitioning is not supported. Do not include partitioning in your SQL Database data model designs.
Data Type support is slightly limited compared to on-premise SQL Server. The most common data types are all fully supported. Geography and geometry data types are also supported.
Details of data type support can be found in the SQL Database documentation on
Data Types and in the discussion of supported/unsupported features in the Azure
One of the chief architectural challenges of a spanning application which combines on-premise code with Azure-hosted databases is the network latency between application code and the Azure database(s). For applications hosted entirely in Windows Azure (at
least within one Azure site), this is largely a non-issue. For more geographically distributed solutions, care should be taken in the code design to minimize the impact of network latency.
Achieving this goal usually means focusing on two things. The first is keeping the number of round trip calls to SQL Database as minimal as possible. The second is keeping the volume of data transferred as small as possible.
Consider the following simple example which shows three different ways of coding to accomplish the same end result. For the sake of illustration, assume you have a single table of messages for your ‘followers’ stored in a SQL Database. Sample 1 shows the
DDL for this table and for two stored procedures which insert data into it.
Sample 1 - Create table and stored procedures
The first stored procedure (usp_AddTweet) is a simple, very typical way of inserting one record. The second stored procedure (usp_AddTweets) accepts a parameter of type table and inserts all items in the table parameter within a single stored procedure call.
Let’s take a look at three ways to add 100 tweets to the TweetLog table.
Sample 2 shows a C# method which inserts 100 tweets by creating an ADO.NET SqlCommand and executing it in a for loop. The content of the tweet is irrelevant, so we just use a meaningless string.
Sample 2 - C# Application Code to Insert 100 Records (In a Loop)
As you might expect, there will be a lot of unnecessary overhead simply performing the round trips to the SQL Database service to invoke the stored procedure 100 times.
Another approach might be to construct a batch of SQL text and submit it to the database in one call. The code in Sample 3 does this, stringing together 100 INSERT statements and then executing the batch in one execution of a SqlCommand.
Sample 3 - C# Application Code to Insert 100 Records (In a Single Batch)
Yet another approach is to use table parameters, a feature introduced in SQL Server 2008. Here, we can call a stored procedure one time with all the data stuffed into a single, structured parameter. In this case, the stored procedure we call is usp_AddTweets,
defined earlier in Sample 1.
A key part of making this work is the object we assign to the ADO.NET SqlParameter for the table parameter. This can be a DataTable, a DataReader, or a custom C# class like the one in this example. Sample 4 provides the code for this approach.
As with the SQL batch example, we are making only one call to the SQL Database in this method.
Sample 4 - C# Application Code to Insert 100 Records (With a Typed Table-valued Parameter)
How do these three examples perform? The table below shows times reported by these code snippets when run from the Eastern United States against the North Central US SQL Database site. Of course, your results will likely vary based on your location, the
target Azure site, and network conditions. The conclusion, however, should keep similar proportions.
The poor performance of the 100 stored procedure calls is not surprising. Perhaps more informative is the superior performance of Sample 4 over the batch of SQL text in Sample 3. Obviously, both benefit from using a single round trip. Sample 4, however,
seems to benefit from more compact payload on the wire and plan optimizations provided by the stored procedure.
Experienced developers will recognize that this is nothing new. It is long held best practice in client server and distributed systems development to minimize round trips between application code and a remote database server. Working over the Internet with
cloud hosted data, however, makes this best practice more important than ever. In fact, it can make or break the viability of an architecture.
Although the example is trivial, the contrast of these three approaches is a useful illustration of options to consider in designing your own code. In particular, stored procedures with table parameters are a very effective technique. Note that there can
be multiple table parameters on a stored procedure. So, for example, a complete header-detail INSERT transaction could be achieved in one procedure call.
The ADO.NET Entity Framework is a part of the .NET Framework which provides a rich set of classes for creating distributed data-sharing applications. Entity Framework fully supports SQL Database, and is a good option for productively creating data access
code which will interact with SQL Database.
Be aware that, when using Entity Framework (EF) with SQL Database, the choice between
Lazy Loading and Eager Loading of related objects can be very impactful if your code will run remotely from SQL Database. Similar to the discussion of latency in the previous section, forcing
EF to minimize round trips with Eager Loading can benefit performance. Of course, the best choice may vary based on the amount of data in your database and the client access patterns.
The following MSDN Magazine article,
found here, offers more information on lazy v. eager loading in EF with SQL Database.
SQL Database supports connections from PHP using the Microsoft Drivers for PHP for SQL Server. Connecting to SQL Database requires providing a connection string which references a SQL Database data source.
See MSDN for the latest information and downloads for this driver.
SQL Database access from Java code, using the Microsoft JDBC driver, has been possible but not supported for some time. As of Feb 2, 2011, an updated version of the SQL Server JDBC 3.0 driver is
available here with full support for SQL Database.
Web services are another important option to consider for Azure access from cross-platform stacks. Probably the best place to start on this path is WCF Data Services (a.k.a. OData). With Windows Azure, you can host any type of web service layer (ASMX
or various WCF channels, for example) to expose SQL Database data.
A key architectural option to consider with SQL Database is scaling out. “Scaling out” means spreading data and processing workload across multiple databases.
There are two main reasons scale-out is especially interesting for SQL Database. The first is that with the current version of SQL Database the maximum size of a database is 150GB. For applications which require more data, the option is to divide the data
into multiple databases which remain within the size limit.
The second reason is that elasticity, a key pillar in cloud-computing’s value proposition. To fully realize this benefit, an application which uses SQL Database can be designed to distribute its data across several physical databases. When
the need for storage capacity and/or processing power is minimal, the number of databases can be ramped down. When the need is high, the number of databases can be ramped up. Ideally, an application could transparently interact with the data regardless of
the number of databases in use. The practical reality today is that this takes work to implement regardless of the architecture, on-premises or cloud-computing.
The current story with respect to scaling out across multiple SQL Databases is to implement a sharded database design. It is in the plan for future releases of SQL Database to introduce a feature called Federation to make such implementations easier.
A ”sharded” database design is one which divides data “horizontally” across databases. If you are familiar with the concept of distributed partitioned views, then you have the basic idea of sharding.
A very thorough discussion of sharding principles and techniques can be found on the SQL Database TechNet Wiki
SQL Database November 2011 release offers Federations in SQL Database. This is intended to provide engine-level support for horizontally scaled databases. Some of the tasks it makes easier are:
For early information on this emerging feature area, see the following links:
The tools for tuning and optimizing a SQL Database workload have some important differences vs. on-premise SQL Server.
Let’s address first those tools that are no longer necessary as the DBMS is hosted on Microsoft-managed servers in the cloud, there is no need to have access to Windows perfmon to peek into the activity on your database. SQL Profiler is unavailable with
SQL Database, and some of the performance related DMVs in on-premise SQL are not exposed by SQL Database.
Several key performance-related DMVs are available, however. These include:
A downloadable whitepaper,
Troubleshooting and Optimizing Queries with SQL Database, provides more information on the available DMVs.
SQL Server Management Studio can be used to view estimated and actual execution plans for queries in SQL Database. The standard IO and CPU statistics in Management Studio are also available. The SET STATISTICS IO and SET STATISTICS TIME options return server
information; the Client Statistics (Query > Include Client Statistics) provide network traffic and latency information.
A common need for solutions which mix on-premise and cloud data stores is the ability to synchronize data between on-premise and cloud databases. SQL Database currently addresses this need with the Microsoft Sync Framework. Sync Framework is a .NET-based
development framework for synchronizing arbitrary data sources. The Sync Framework
Developer Center is a good starting point for resources on this technology.
The bottom line is simple: Sync Framework is the tool recommended to synchronizing on-premise data with SQL Database. Project teams will require .NET development skills to implement data synchronization functionality. Microsoft is investing in expanding
and improving the capabilities of Sync Framework when used with SQL Database. Hence, there are some features that SQL Database does not support, such as SQL Replication or Linked Servers. Distributed transactions are also not supported with SQL Database.
While a DBA or SQL-focused developer can configure Replication and other SQL-centric technologies, Sync Framework is currently squarely focused on the .NET developer.
You can also use BCP.exe or SSIS packages to synchronize data between on-premise SQL Server and SQL Database. These may or may not be practical depending on the nature of sync. There are situations where data in SQL Database needs to be sync’d back to SQL
Server on premise and all data in SQL Database wiped out; BCP and SSIS are great tools in those scenarios.
As of first half of calendar year 2011, there is a more complete service by invitation-only CTP (click here to register) called SQL Data Sync, which will do both on-premise-to-cloud and cloud-to-cloud
synchronization. This is built, of course, atop the Sync Framework. But it removes the need to write code to initiate, configure, and schedule synchronization, instead providing a complete user interface for these tasks. For more information, check out this
Sample 5 shows a minimal code example for performing synchronization between an on-premise SQL Server database and SQL Database using the current version of Microsoft Sync Framework. Two key things to be aware of early when looking at Sync Framework are:
Much more extensive samples are available at the
Sync Framework Developer Center.
Sample 5 - Basic Synchronization with Microsoft Sync Framework 2.1
One point to note with Microsoft Sync is that the technology creates/adds some tracking tables to your databases in SQL Database as part of its synchronization and this eats into the database space usage of SQL Database. So you should test your scenario
before deciding this approach.
With databases deployed in remote data centers, a natural question, especially for enterprise customers, will be how to perform geo-replication of data across distinct data centers. Key motivations for this include disaster tolerance and placing data closer
to users in different regions. With SQL Database the story is based on the Microsoft Sync Framework.
Fundamentally, the Sync Framework can synchronize between two Azure-hosted databases, wherever they are, in exactly the same way it works between an on-premise and an Azure database. The only difference is the connection strings. There are three potential
approaches to doing this. They are distinguished only by how and where the code which uses Sync Framework is hosted.
In the latter half of 2011 SQL Data Sync will become generally available with the features that were released in CTP1 and CTP2, i.e synchronizing between SQL Databases and synchronizing between SQL Database and on-premises databases.
Most SQL error handling practices are no different with SQL Database as compared to on-premise SQL Server. There are a few error conditions, however, which are unique to SQL Database.
Throttling: As a multi-tenant data platform service, SQL Database has safeguards in place to prevent runaway resource usage, which would affect other users. In the case of excessive usage of CPU, memory, tempdb, transaction log, or IO, SQL
Database will “throttle” the offending connection by throwing error 40501 and terminating the connection. The text of the error message will include a reason code that can be parsed to determine the throttled resource.
Connection Termination: SQL Database may also terminate a connection with other error codes due to extended inactivity, long-running transactions, etc.
Database size limits: if a database reaches its maximum configured size, any operation which will add more data fail with error 40544. You can resolve this error by reducing the amount of data in the database or using the ALTER DATABASE
statement to increase the maximum size (up to the service maximum of 150GB). Bear in mind that growing the database into the next size tier will increase the daily cost of that database.
Since many of these Azure-specific error conditions may result in connection termination, custom code which uses SQL Database should implement a connection retry mechanism in its exception handling code.
For a complete error code reference, see
Error Messages (SQL Database) in the online documentation.
To aid in troubleshooting and support, SQL Database assigns a session trace id for every connection. This id is a GUID, and can be retrieved using the Transact-SQL CONTEXT_INFO() function. For example:
SELECT CONVERT(NVARCHAR(36), CONTEXT_INFO())
Besides usefulness in your own debugging, this id can also be provided to Microsoft customer support to help track down problems. It is a good idea to capture this as a matter of course in your custom data access code.
CONTEXT_INFO can also be read from the sys.dm_exec_sessions and sys.dm_exec_requests DMVs, which can allow visibility of the trace id for other active sessions.
The relational database engine provided by SQL Database is a great tool for storing, querying, and managing data in the cloud. A SQL TDS connection may not, however, be the ideal connectivity model for expected consumers of your data. For many scenarios,
web service is a better way to expose data to its consumers, even if the data is stored in SQL Database. Usually, Windows Azure is the best host for the web services code itself.
Any form of .NET based web service – WCF or ASMX – can be hosted in a Windows Azure web role to serve as an access point for SQL Database data. Besides providing a flexible protocol (i.e., HTTP vs. TDS) this can also provide more authentication options than
just SQL logins with username/password.
Open Data Protocol (OData) is an especially interesting option for web service access to SQL Database data.
OData is a standards-based protocol for querying and updating data. OData is supported in the .NET Framework through
this blog entry illustrates, it is a simple matter to hang an OData service in front of SQL Database data. Keep in mind that if the Windows Azure web role is hosted in the same data center as the SQL Database, bandwidth between the two components is free
(see the session Data Transfers).
Another, even easier way to put an OData face on your SQL Database data is with the pre-release
SQL Database OData Service at SQL Database Labs.
Server Management Objects (as of SQL Server 2008 R2) is partially enabled for use with SQL Database. Guidance from the product team is that SMO is not currently intended for use by applications. Rather, it has the limited support necessary to manage SQL
Database through SSMS 2008 R2.
SMO can be used for basic interrogation, management, and scripting of SQL Databases. Keep in mind, though, that there are limitations on SMO support for SQL Database.
For additional info see the section on SMO at
Tools and Utilities Support (SQL Database) in the online documentation.
The fact that SQL Database resides ‘in the cloud’ in a Microsoft data center naturally changes some of the techniques and considerations for deploying and securing databases. This section addresses deployment and security for SQL Databases.
After a server is created in SQL Database, that server is, by default, not accessible for any external connections. One or more firewall rules must be configured to allow outside connection to the server’s databases.
A firewall rule consists of a rule name and an IP address range. The range can cover multiple addresses (e.g., 22.214.171.124 - 126.96.36.199) or just a single address (e.g., 188.8.131.52 - 184.108.40.206). Rules can be added via the Windows Azure Management
Portal or with stored procedures. Note that, currently, the first rule must be added from the portal, since the ability of a program to access SQL Database and invoke the stored procedures presupposes access through the firewall.
To add a rule using the management portal, select the server for the subscription of interest and locate the Firewall Rules button in the server information section of the central pane (see Figure 8).
Figure 8 - Firewall Rule Management in the Windows Azure Management Portal
Click the button to expand the firewall rules table and click the Add button. The Add Firewall Rule dialog, shown in Figure 9, will pop up. Provide a name and the start and end IP addresses for the range which will be allowed to access the server. Click
OK and the rule will be created.
Figure 9 - Defining a Firewall Rule
The rule may take a few minutes to become effective on the Internet facing Azure firewalls.
Firewall rules may also be added, changed, or deleted with T-SQL using the system stored procedures sp_set_firewall_rule and sp_delete_firewall_rule. For example, the following command would create a firewall rule for a certain range of addresses:
exec sp_set_firewall_rule 'PhoenixOffice', '220.127.116.11', '18.104.22.168'
Note that access to your SQL Database server from other Windows Azure services – code in a Windows Azure web role, for example – is also disallowed by default. To allow access from within Windows Azure, you can check the box labeled “Allow other Windows
Azure services to access this server” on the management portal (see Figure 8) or add a rule with an IP address range of 0.0.0.0 – 0.0.0.0
exec sp_set_firewall_rule 'Windows Azure', '0.0.0.0', '0.0.0.0'
Unlike on-premise SQL Server, SQL Database does not support Windows authentication. Traditional SQL authentication based on username and password is the only supported authentication type. This due to the fact the SQL Database servers are in the cloud with
no trust relationship to a specific AD forest’s domain controllers.
Nevertheless, dependence on SQL authentication can be inconvenient in some scenarios. You may wish to explore some type of username/password broker component in your solution that leverages AD single-sign-on to provide a client with SQL Database username
and password. For multi-organizational solutions, Windows Azure AppFabric as a federated identity authority might be useful. In such a scenario, authentication against AppFabric may be used to get access to login credentials for SQL Database.
Server Level Roles.
SQL Database does not have the fixed server roles found in on-premise SQL Server. Instead, there are two special database roles present in the master database which impart special administrative permissions.
Note that there is no sysadmin role. The closest equivalent to this role in SQL Database is the “server level principal login”, which is analogous to
sa in on-premise SQL Server. This principal is set up when the SQL Database account is provisioned.
Database Level Roles
The fixed database roles in SQL Database are identical to those in on-premise SQL Server.
Discretionary Access Control
Within an individual database, the discretionary access control model for GRANT-ing (or DENY-ing) specific permissions on objects or statements is essentially the same as it is in on-premise SQL Server.
Connecting to SQL Database from ADO.NET, ODBC, or PHP requires the standard connection string format used by the respective library. There are a few fine points to constructing a connection string for SQL Database, however. Depending on the configuration
on the client machine and the tools used, it may not always be required to adhere to all of them – but, it will not hurt.
The Windows Azure Management Portal provides a handy method to get a proper connection string for connecting to your SQL Database. From within the portal, select SQL Database (the Database icon in the left-hand pane) and highlight the database for which
you need a connection string. The Properties viewer in the right-hand pane (see Figure 10) will include an item for “Connection Strings.” Click the ellipsis button and a pop-up will provide fully formed connection strings for ADO.NET, ODBC, and PHP.
Figure 10 – Connection Strings Provided by the Management Portal
As with any use of SQL Server, connection string details should always be managed securely. The connections string or it constituent details should be secured so that only authorized principals may access it. Where feasible, encryption should also be used
to protect the connection string information.
Options for auditing access to SQL Databases are currently limited. Successful and/or failed logins cannot be audited. The SQL Server Audit feature is not supported. Also, SQL Trace is not supported by SQL Database.
Standard DML triggers on tables (i.e., INSERT, UPDATE, DELETE triggers) are supported and can be used to track changes to data. Also, a subset of server and database DDL triggers are supported. These also can be used to audit certain administrative or application
If it becomes necessary to change the password for an existing login, the only currently supported method is T-SQL. The syntax to change the password for an existing login is as follows:
ALTER LOGIN login_name WTH PASSWORD =
This command can only be executed within the master database.
In many cases the development of a solution will be done with on-premise SQL Server, prior to production deployment to SQL Database. Or, an existing solution may need to be ported from on-premise SQL to SQL Database. Moving the schema and code to SQL Database
can be accomplished by scripting the database with SQL Server Management Studio 2008 R2 (SSMS).
Special care, however, is required to ensure the script will work on SQL Database. Since there are small differences in the T-SQL syntax supported by SQL Database and on-premise SQL Server, SSMS must be told to generate a script which is compatible with
As shown in Figure 11, this is done from the Set Scripting Options page in the SSMS Generate Scripts wizard. On that page, click the
Advanced button to display the Advanced Scripting Options dialog box. On this dialog, set the “Script for the database engine type” option to “SQL Database”. Note that this option is only available in the R2 version of SQL
Server 2008 Management Studio.
Figure 11 - Selecting SQL Database as the Engine Type to Script For
You can also use the Generate Scripts wizard to script data to be loaded into your SQL Database. Also in the Advanced Scripting Options dialog is an option named “Types of data to script” (Figure 12).
Figure 12 - Scripting Schema and Data for Transfer to SQL Database
If this option is set to “Schema and data”, SSMS will include INSERT statements for all records in the generated script. While this is handy for smaller databases, it becomes inefficient and unwieldy for large databases. For large databases, it is usually
better to use the options described in the following section “Moving Data into SQL Database”.
SQL Database supports the following tools for efficient data loading into a SQL Database:
One of these options is usually the best choice for loading significant amounts of data into SQL Database from an on-premise source. Good information on best practices for using these tools with SQL Database can be found in the following blogs and articles:
Finally, a good end-to-end demonstration of using these techniques can be found at the following link:
Import Export can be used as a client side tool, or as a cloud service. There are open source samples showing how to perform both on premise to cloud, and cloud back to on premise.
SQL Server Migration Assistant 4.2 was updated in 2010 to support migration of Microsoft Access databases (version 97 or later) to SQL Database, as well as to on-premise SQL Server 2008. This tool has a migration wizard for transferring the
structure and data from a local Access database to an existing SQL Database. For Access objects which cannot be directly migrated (for example, certain kinds of Queries) SSMA produces a report detailing the items which require manual attention.
SSMA 2008 for Access 4.2 is a tool for performing migrations of the data store from small departmental applications to SQL Database. It can be downloaded
here. Note that only the SSMA 2008 installer includes support for SQL Database.
A clear and simple, end-to-end walkthrough of using SSMA 22008 for Access with SQL Database can be found at this link:
Migrating Microsoft Access Applications to SQL Database.
Also, note that there is another version of SSMA 2008 aimed at MySQL, which can be used for migration from MySQL databases to SQL Database. It can be downloaded
Data Tier Applications (“DAC” for short) are a construct introduced in SQL Server 2008 R2, with developer tool support in Visual Studio 2010. They are useful for packaging the schema, code, and configuration requirements of a database for deployment to another
server (for example, a staging or production server).
The Azure SQL Import Export service uses DAC technology to build the artifact for moving data and schema to the cloud. The extension is .BACPAC for data + schema.
Once your SQL Database is in production, there are certain tasks required for ongoing maintenance. As discussed in the Planning section of this document, SQL Database inherently eliminates a broad swath of traditional maintenance issues. However, there are
some standard tasks, like index and statistics maintenance, that apply in SQL Database just as in on-premise SQL Server. Other typical tasks still apply must be handled differently.
In some cases, entirely new aspects of maintenance or operations come into play with SQL Database. Tracking usage and billing using Azure DMV’s is one example.
For the latest information on SQL Database backup and restore strategy and disaster recovery techniques, see
Business Continuity in Windows Azure SQL Database article in the Windows Azure SQL Database MSDN library.
Native backup and restore as provided by on-premise SQL Server is not currently supported by SQL Database. This is however on the roadmap and a preview of this feature is expected by middle of calendar year 2011.
The Azure SQL Database Import Export service allows you to make a complete copy of your database and place it into your blob storage. This service is provided
at no additional cost to customers. You do have to pay for the storage used in your storage account.
SQL Database natively supports a Database Copy capability. This creates a new database in SQL Database which is a transactionally consistent copy of an existing database. This is accomplished using special syntax within the CREATE DATABASE command:
CREATE DATABASE destination_database_name AS COPY OF
As the optional server name in the syntax implies, this can be used to create a copy of a database on the same server, or on a new server. The new server can be owned by another Azure account, but for the copy to work some special rules must be adhered to
(see the documentation, referenced below).
The user executing this statement must be in the dbmanager role on the target server (to create a new database) and must be db owner in the source database.
For full discussion of this feature, see
Copying Databases in Windows Azure SQL Database.
The data in a SQL Database can be backed up on-premise, or to another SQL Database, using BCP, SSIS, or the .NET SqlBulkCopy API. Obviously, these approaches do not backup the structure and objects in the database, so you will need to generate build scripts
to accompany the data if you wish to bootstrap the database into a new environment.
For a thorough discussion of the options for moving data in bulk out of (or into) a SQL Database, see
this blog post from Microsoft SQL Customer Advisory Team, and this
this discussion of BCP specifically.
In SQL Database, as with on-premise SQL Server, indexes can become fragmented over time. They should be periodically checked and, if necessary, rebuilt. The
syntax for the ALTER INDEX statement is restricted in SQL Database, as compared to on-premise SQL Server, but the syntax for rebuilding indexes is identical.
Reorganizing indexes is not supported by SQL Database.
Both online and offline index rebuilds are supported by SQL Database.
Another routine maintenance task in SQL Server is keeping statistics current. There are no significant differences in statistics management between SQL Database and on-premise SQL Server. The following are supported:
The ALTER DATABASE statement, however, cannot be used to change the database-level settings automatic statistics creation and updating. These settings both default to True (ON) for SQL Databases and they cannot be changed. If you truly find it necessary
to suppress auto stats updates, use the sp_autostats stored procedure to control this behavior at the table/index level. In the vast majority of circumstances, you can just leave the auto update behavior unchanged.
Depending on the subscription model used by your customer, SQL Database may be billed on a consumption basis. This makes it valuable to track consumption of bandwidth and space on an ongoing basis. Although there are reports within the Azure billing portal
which help track this, customers often wish to do some kind of customized tracking of usage expense. SQL Database provides DMV’s to enable this.
Bandwidth usage from your SQL Database account is available in a DMV called
sys.bandwidth_usage. This DMV is only available in the master database. Since three-part names are invalid in SQL Database, you will need to be connected to the master database to query the
sys.bandwidth_usage view. An example of the resultset returned by this view is shown below in figure 13. The quantity column is in kilobytes.
Figure 13 – Result set from sys.bandwidth_usage. Quantity column in KB
Database usage is available in a DMV called sys.database_usage. This DMV is also available only in the master database. An example result set is shown in Figure 14.
Note that the quantity here is rolled up across databases. For example, in the sample listing below, the quantity of 1 was reported for one 1GB database. The quantity of 2 is reported for a two 2GB databases. If, on a certain day there was one 5GB database
in use, the DMV would report a quantity of 5.
Figure 14 - Result set from sys.database_usage
SELECT (8.0 * SUM(reserved_page_count)) / 1024 AS 'Database Size (MB)'FROM
This query reports on the current database only, so you will need to run it while connected to the specific database you are interested in. Note that permission on
sys.dm_db_partition_stats is denied in the master database, even for administrators.
A common need in production SQL Server systems is finding the root cause of blocking problems. In SQL Database some of the familiar tools for doing this – sp_who2, SSMS Activity Monitor – are not available. The DMVs exposed by SQL Database can, however,
help fill this need.
blog entry demonstrates a DMV query for identifying blocked/blocking processes.
whitepaper discusses the available DMVs for performance for troubleshooting.
Also see Monitoring Windows Azure SQL Database Using Dynamic Management Views.
Scheduling maintenance (e.g., index reorganization) will sometimes be required, especially for large or heavily accessed SQL Databases. Unfortunately, SQL Server Agent, the on-premise SQL Server scheduling engine, is not part of SQL Database. This means
there is no Azure-hosted method for scheduling tasks to occur.
For the time being, the only way to address this requirement is with an on-premise or non-Azure scheduling tool. A natural choice is, of course, an on-premise instance of SQL Server Agent. This works perfectly well and will make SQL Server DBA’s comfortable.
Using on-premise SQL Agent is OK for customers with existing SQL Server infrastructure. Those with no existing SQL licenses, however, may wish to avoid buying database software just to get a scheduling engine. In this case, Windows Task Scheduler can be
used to invoke sqlcmd scripts, Powershell scripts, or custom executables which reach out to SQL Databases to perform maintenance tasks.
Finally, there is no reason third-party task scheduling cannot be used, if the customer already has it and is comfortable with it.
A References section with links to SQL Database MSDN, SQL Database team blogs, customer case studies is a good way to end the WP.
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