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- Retired : Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI DP500
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Imagine orchestrating a symphony of data, where every note is a piece of valuable information harmonised in a seamless flow. Welcome to the world of Azure SQL Database, where cloud computing meets efficient Data Management. In today’s data-driven era, businesses face the challenge of handling massive amounts of data generated from various devices. That’s where this platform comes in to save your day.
This robust platform, designed for modern web applications, is renowned for its efficiency and ranks among the top database management systems. Let’s delve in deeper to learn more!
Table of Contents
1) What is Azure SQL Database?
2) Azure SQL vs SQL Server
3) Azure SQL – Architecture and its types
4) Azure SQL services
5) Azure SQL Database features
6) Azure SQL Database tiers
7) Advantages of Azure SQL Database
8) Microsoft Azure SQL pricing
9) Career and certification in Azure SQL
10) How to create and manage Azure SQL resources in the Azure portal?
11) Conclusion
What is Azure SQL Database?
Database as a Service (DBaaS) supports both SQL and NoSQL along with other Databases (DB) like Azure Cosmos DB, PostgreSQL, and Azure SQL. Azure SQL Databases offers integrated, hybrid and migration features. It provides backup, automation, site recovery, and monitoring DB activities with the help of Cloud administration and tools. To leverage these features effectively, understanding Microsoft Azure can enhance your ability to manage and optimize your database solutions.
Azure SQL Database is a reliable and scalable Database as a Service (DaaS) with fully automated, AI-powered solutions. Azure Database makes it possible to host and utilise a relational SQL Database in the Cloud without the need to install any hardware or software. The Database can also be expanded and contracted in accordance with corporate requirements. Azure SQL supports all relational, XML, JSON, and spatial data sets.
Azure SQL vs SQL Server
Here are the key differences between Azure SQL vs SQL Server:
Azure SQL |
SQL Server |
A single Database is capable of hosting multiple Databases from various customers. |
Databases are considered the only objects residing on the server. |
Azure SQL utilises the Tabular Data Stream or TDS protocol. |
SQL Server utilises the TCP/IP protocol for communication purposes. |
Azure SQL does not support direct communication because of its complex architecture. |
SQL Server supports direct communication because of its simple architecture. |
Azure SQL makes managing and administering data easy. |
SQL Server is difficult to set up and administer. |
Azure SQL is easy to use as users do not require any physical hardware. |
SQL Server needs a physical system, which makes data operations cumbersome. |
Azure SQL enables the automatic backup of data. |
SQL Server only supports manual scheduling of its data backup |
Azure SQL – Architecture and its types
Azure SQL Database provides intelligent, well-managed database services with serverless computing that supports Cloud applications. Azure Cloud SQL Database, as PaaS, makes it easier to install software, handle patches, and maintain servers in the cloud, as it doesn’t require a software licence or version. Azure Data Factory can further enhance your data integration and transformation processes, complementing the capabilities of Microsoft Azure Database, which is a highly scalable and multi-tenant relational database service available in the cloud. The architecture layer of Azure SQL DB is of three types. They are:
a) Client layer: The client layer functions as a User Interface (UI) for applications that access SQL Database. Data transmission occurs between the SQL Database and applications. TDS communication is used in SQL DB with ODBC, .NET and ADO.NET technologies to connect with software applications.
b) Service layer: The service layer is in between the platform layer and the client layer. It serves as a secure gateway between them. Provisioning, billing, and other routing connections fall under this layer. It can implement SQL database validation rules as well as user access authentication.
c) Platform layer: The platform layer has system data nodes by which we can host the SQL database on the physical server. Multiple copies of servers can be maintained within the Azure Cloud. Additionally, it creates a connection between the application and the SQL Database. It makes sure that when clients modify their data on them, the copies are kept synchronised.
There is another layer called the infrastructure layer that oversees managing the Operating System (OS) and physical hardware
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Azure SQL services
Now, we will move on to discuss the services offered by Azure SQL:
Deployment in Azure SQL Database
Deployment is the process through which developers work on their products to update the application module and patch distribution to make it available for the users. In the Microsoft SQL Database, deployment is of three types. They are:
1) A Single Database is an isolated, fully maintained Database. Single Databases are preferred in cloud apps and microservices that require a secure data source.
2) An elastic pool is a group of individual Databases that share a common set of resources, like memory or CPU. A single Database can be added to or removed from an elastic pool.
3) Azure SQL Managed Instances (MI) are enterprise editions of a recent SQL server used in the on-premises Database. They let you set up a Virtual Network (VNet) that replicates on-premises deployments and boosts security. Azure SQL Managed Instance is a PaaS Database that offers automatic backup and autoscaling features. For enhanced security and identity management, integrating Azure Active Directory can provide comprehensive access control and authentication for your managed instances.
Service tiers in Azure SQL
The deployments mentioned above allow us to use Azure SQL service tiers. Azure Cloud Database's three service tiers are as follows:
1) The general-purpose service tier allows you to create apps by using a single Database. You can modify this service tier at any time manually or programmatically based on your needs. It has good performance as it runs without causing any downtime to apps or customers.
2) The business critical/ premium service tier assists you in Online Transaction Processing (OLTP) services. It focuses on transactions and latent periods in business transactions. It provides maximum resilience to failures. To further enhance the security and reliability of your OLTP services, integrating Azure Security Tools can offer robust protection against potential threats and vulnerabilities.
3) The Hyperscale service tier is specially designed for business workloads. Through the use of independently scalable computation and storage resources, it offers excellent flexibility and high performance. By enabling this service, you can deploy a Database replica. It provides greater resilience to failures.
Computational models in Azure SQL Database
In the above-mentioned three deployments of Microsoft SQL, you can choose between two computational models. They are:
1) Provisioned computation: You can use your Database with the selected Azure SQL service.
2) Serverless computation: This allows you to operate your Database as a serverless segment. It uses an auto-scaling method to compute volumes. They are charged per second.
Having known about the deployment models, service tiers, and computational methods, now let’s see in detail about Auto scalability and performance.
1) Service-based criteria scale automatically, whereas dynamic scalability enables manual scaling without service interruption.
2) Make use of the serverless tier, which has auto-scale.
3) Schedule or automate scalability for a single Database using scripts.
4) PowerShell is used for monitoring and scaling a single Database.
5) Use elastic pools for specific needs.
6) You may schedule or automate scaling for elastic pools by using custom scripts.
Azure SQL tools
Azure SQL Database can be used both in Azure and on-premises with Azure Arc. It has features for data discovery, Machine Learning, built-in security, scalability, and easy data migration. For simple applications single Database is used, and for multi-tenant applications, an elastic pool is used. To complement these capabilities with serverless compute options, you can integrate Azure Functions for automating tasks and extending your database functionalities.
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Azure SQL Database features
The Azure SQL Database offers you a range of features that are designed to simplify the process of management. Here is a list of its features with a brief explanation of each:
1) Scalability: Quickly scale your Database resources by increasing or decreasing them to meet the requirements and avoiding downtime.
2) High availability: Take advantage of the same high availability built-in and automatic backups, ensure safekeeping of your data.
3) Security: Use top of the class security features like encryption, threat detection, and access control in order to protect your data.
4) Intelligence: Apply intelligent query processing for better query performance and auto-tuning for the best possible query execution.
5) Compatibility: Seamlessly migrate your existing SQL Server applications to the Azure SQL Database with minimum changes needed.
6) Cost-efficiency: Cost-optimisation with pay-as-you-go pricing models that are scalable.
Azure SQL Database tiers
Microsoft Azure SQL Database offers multiple service tiers with options for workload variability and budget considerations. Every tier includes a specific combination of computing, storage, and I/O resources, allowing you to configure your Database for optimal efficiency and cost. The following tiers are explained briefly below:
1) Basic tier: Engineered to tackle light tasks and small Databases and providing the most affordable entry point to Azure SQL Database with basic characteristics.
2) Standard tier: Provide balanced performance and storage, suitable for the middle-sized Database and moderate workloads that are capable of more than the Basic tier.
3) Premium tier: Designed for high performance needs and with advanced features, high throughput and low latency, which is the ideal solution for critical applications and heavy workloads.
4) General purpose tier: Offers good balance between cost and performance, and can work with multiple kind of workload, providing both flexibility and scalability.
5) Hyperscale tier: The architecture is built for huge scalability and performance, mainly suitable for instances with unpredictable workloads or heavy analytical processing.
Advantages of Azure SQL Database
Here are some important advantages of using Azure SQL Database:
1) It has long-term backup (up to 10 years) and automated backups.
2) By using geo-replication, you can access secondary Databases at data centre locations.
3) Automatic tuning is a performance tuning tool powered by AI to automatically correct performance issues.
4) High availability, built-in intelligence, and easy-to-use tools.
5) One of the best features is scaling Database resources (scale up or scale down).
6) More deploying models.
7) Effective monitoring and alerting tools.
Advanced security and compliance
Here are some important advantages of using Azure SQL Database:
1) It has long-term backup (up to 10 years) and automated backups.
2) By using geo-replication, you can access secondary Databases at data centre locations.
3) Automatic tuning is a performance tuning tool powered by AI to automatically correct performance issues.
4) High availability, built-in intelligence, and easy-to-use tools.
5) One of the best features is scaling Database resources (scale up or scale down).
6) More deploying models.
7) Effective monitoring and alerting tools.
Microsoft Azure SQL pricing
Azure SQL Database allows its users to purchase a PaaS Database engine that fits their requirements. You can pick a purchase strategy that works for you based on the Azure SQL Database deployment model. SQL Database offers the following purchasing models:
A) vCore-based purchase model:
1) In the vCore-based purchase model, you can choose the number of vCores, the storage quantity, and the size and speed of storage.
2) With the vCore-based purchasing model, you can also use the Hybrid Benefit for Azure SQL Server to reduce costs.
3) The vCore- based purchasing model, is for clients who prefer flexibility, transparency, and control.
4) The pricing of vCore starts at £365.90/month for 10.2 GB of memory.
B) Database Transition Unit (DTU)-based purchasing model:
1) The DTU -based purchasing model, supports the workloads in the Database for all three service tiers.
2) It takes care of the computation, storage, and I/O resources in the service tiers.
3) The DTU-based purchasing model is best for users who need a simple and preconfigured resource approach.
4) The pricing of vCore starts at £365.90/month for 10.2 GB of memory.
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Career and certification in Azure SQL
SQL Developer is one of the most in-demand careers due to the exponential growth in data and information. Azure SQL Database is a potent Database engine that offers professionals excellent pay, in-demand job opportunities, exposure to cutting-edge technology, and attractive career growth.
Microsoft offers the following exams and certifications for aspirants in Azure SQL Database services.
1) Exam DP-300: Administering Microsoft Azure SQL Solutions
2) Exam DP-203: Microsoft Azure Data Engineer Associate
Key roles of an Azure Data Engineer
1) Writing relational Database queries and ER diagrams
2) The preservation of referential integrity for Database objects
3) Creating, launching, and maintaining Databases
4) Participating in data warehouse creation and maintenance
5) Create, and release SSIS packages
6) Reporting production and deployment
7) Assist the team with technical design and coding so that the project deliverables are completed as planned and specified.
8) Capacity to communicate with clients and understand business requirements
Further, let's discuss the salary based on work experience:
Role |
Category |
Salary |
Beginner |
£49,631 /year |
|
Intermediate |
£66,206 / year |
|
Advanced |
£69,612 / year |
|
Beginner |
£39,389 / year |
|
Intermediate |
£44,104 / year |
|
Advanced |
£59,867 / year |
Source: Glassdoor
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How to create and manage Azure SQL resources in the Azure portal?
Creating and managing Azure SQL resources in the Azure portal involves several steps, including tagging resource groups. You can also export your resource groups to templates, choose the correct export option, and understand some export limitations. Let’s see how you can do it:
Tagging resource groups
It is a very important practice if you can organise and manage your resources efficiently. These tags allow you to assign mandates to your resources, which helps you to sort, filter and manage them in complex environments with several resources. Utilizing this approach can significantly enhance the Microsoft Azure Benefits you experience by improving resource management and operational efficiency.
If you want to tag a resource group in Azure, then you can follow these steps:
a) Go to the “Resource Groups”
b) Then select the resource group which you want to tag
c) Then click on the “Tags” tab
d) Then, you can add the key-value pairs, which will help you to assign them to your resource group
e) There are common tags which include environment names such as “prod” for production, “dev” for development, etc. These also include project names, cost centres, and owners.
Tagging aids in cost management, governance, and operational efficiency. By using tags, you can easily identify resources for billing purposes, enforce policy compliance (e.g., ensuring all resources have an owner), and automate resource lifecycle management.
Exporting resource groups to templates
Exporting resource groups to templates is a powerful feature in Azure because it allows you to capture the state of a resource group as a reusable template. This template is in JSON format, which can then be used to deploy your resources consistently across several environments or subscriptions.
Here are some steps that you can follow to export resource groups:
a) Go to the resource group in the Azure portal
b) Then, click on “Expert Template”, which you can find in the overview section
c) Then Azure will analyse the resource group which will in turn generate a template. This represents the present state of all resources in the group.
Choosing the correct export option
When exporting a resource group to a template, Azure offers several options:
a) Exports every resource within the resource group, capturing the entire state as is. Useful for complete backups or migrations.
b) Exports only the resources that have been modified or added since the last export. This is more efficient for ongoing development or continuous deployment scenarios.
The choice between complete and incremental mode depends on your use case. For creating a baseline template or migrating resources, complete mode is appropriate. For iterative development and deployment, incremental mode can save time and reduce complexity.
Some export limitations
While exporting resource groups to templates there are some limitations to be aware of:
a) Complexity in templates: Some Azure resources can have complex configurations that may not be fully captured or are difficult to parameterise in a template.
b) Dependencies: The exported template might not always accurately capture the dependencies between resources, which can lead to deployment errors if not manually corrected.
c) Customisations: Customisations or configurations done outside of the Azure Resource Manager (e.g., direct modifications within the resource itself) may not be reflected in the exported template.
However, you can overcome these limitations. It is crucial that you review and edit the template manually. You need to understand that the structure of Azure Resource Manager template and the configuration of your resource is important. You need to also use Azure policy to enforce the standard configurations which will help you reduce the complexity of resources, thus making the resources easy to manage and report.
Conclusion
We hope that you have understood Microsoft Azure SQL Database and its various features, components, architecture, and services. Azure SQL is designed as a complete package of a Platform as a Service or PaaS and other Microsoft services. There are powerful capabilities which are built into the Database that enable users to devote their time to domain-centric Database administration and activities for optimising their business workflow.
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Frequently Asked Questions
Yes, Azure SQL Database integrates with several analytics tools for business insights, including Azure Synapse Analytics for Big Data and advanced analytics, Power BI for data visualisation and reporting, and Azure Machine Learning for both predictive analytics and Machine Learning models. These tools help derive valuable insights from your data efficiently.
Azure SQL Database supports disaster recovery and business continuity through built-in features such as automated backups, point-in-time restores, active geo-replication, and auto-failover groups. These capabilities ensure data protection, quick recovery from failures, and minimal downtime.
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