- A globally distributed, multi-model database service.
- Can elastically and independently scale throughput and storage across any number of Azure regions . worldwide.
- Take advantage of fast, single-digit-millisecond data access by using any one of the API's.
- Provides comprehensive service level agreements for throughput, latency, availability, and consistency guarantees.
- Supports schema-less data, which you build highly responsive and "Always On" applications to support constantly changing data.
- At the lowest level, Azure Cosmos DB stores in atom-record-sequences (ARS) format.
- Data is then abstracted and projected as an API, which you can specify when you're creating your DB.
- Choices include SQL, MongoDB, Cassandra, Tables, and Gremlin.
- This level of flexibility means that as you migrate your company's DB to Azure Cosmos DB, your devs > can stick with the API that they're most comfortable with.
- A relational DB based on the latest stable version of the Microsoft SQL Server DB engine.
- SQL DB is a high-performance, reliable, fully managed, and secure DB.
- Can be used to build data-driven applications and websites in the programming language of your choice, without needing to manage infrastructure.
- Azure SQL DB is a PaaS DB engine. It handles most of the DB mgmt functions, such as upgrading, patching, backups, and monitoring, without user involvement.
- Provides 99.99% availability.
- PaaS capabilities that are built into SQL DB enable you to focus on the domain-specific DB administration and optimization activities that are critical for you business.
- SQL DB is a fully managed service that has built-in high availability, backups, and other common > maintenance operations.
- Microsoft handles all updates to the SQL and OS, you don't have to manage the underlying infrastructure.
- Azure DB Migration Service can be used to migrate existing SQL Server DBs with minimal downtime.
- The Microsoft Data Migration Assistant can generate assessment reports that provide recommendations to help you guide you through required changes prior to migration.
- Azure DB Migration Service performs all of the required steps, you just change the connection strings in your apps.
- Sign in to Azure Portal
- Create A Resource > Databases > SQL Databases
- Fill in the following:
- Subscription
- Resource Group
- Database Name
- Server
- Fill in the following:
- Select 'Create New"
- New server panel appears
- Fill in the following:
- Server Name
- Server Admin Login
- Password
- Location
- Fill in the following:
- 'Next: Networking'
- Fill in the following:
- Connectivity Method
- Fill in the following:
- 'Next: Security'
- Select 'Not Now' for Azure Defender for SQL
- 'Next: Additional Settings'
- Fill in the following:
- Data Resources
- Use Existing Data (Sample)
- Collation (Default)
- Fill in the following:
- 'Review + Create'
- After validation success, on the 'Create SQL Database window, select 'Create' to deploy the server and database. (2-5 mins)
- Select 'Go to Resource'
- Select 'Set Server Firewall', select 'Yes' to 'Allow Azure services and resources to access this server
- Save
- Select 'Ok'
- From 'All Resources' pane, search and select 'SQL Databases', ensuring your new DB was created (may need to refresh).
- Select 'db1' representing the SQL db you created, and then select 'Query Editor (preview)'
- Sign in (You shouldn't be able to)
- Select Overview > Set Server Firewall
- In 'Client IP Address', you IP will be shown (verify). Click on '+ Add Client IP', which will add a 'Rule Name' and put your IP in both the 'Start IP' and 'End IP' fields, then 'Save'.
- Return to SQL DB and the Query Editor sign-in page. Sign in should succeed this time.
- Repeat Step 7 if you still cannot login.
- Enter the following in the editor pan:
- SELECT TOP 20 pc.Name as CategoryName, p.name as ProductName
- FROM SalesLT.ProductCategory pc
- JOIN SalesLT.Product p
- ON pc.productcategoryid = p.productcategoryid; 9 'Run', then review query results in the 'Results' pane.
- Azure Db for MySQL is a relational db service in the cloud, and it is currently based on the MySQL Community Edition db engine, versions 5.6, 5.7, and 8.0.
- 99.99% availability SLA form Azure.
- Built-in security, fault tolerance and data protection.
- Built-in high availability with no additional cost. - Predictable performance and inclusive, pay-as-you-go pricing. - Scale as needed, within seconds. - Ability to protect sensitive data at-rest and in-motion. - Automatic backups. - Enterprise-grade security and compliance. - This is all provided at no additional cost with almost no required administration.
- Azure DB for PostgreSQL is a relational db service in the cloud.
- Based on the community version of the open-source PostgreSQL db engine.
- Built-in high-av compare to on-prem resources. No additional config, replication or cost required.
- Simple/Flexible pricing, predictable performance based on selected pricing tier choice that includes software patching, automatic backups, monitoring, and security.
- Scale up/down as needed in seconds, adapting services to match usage.
- Adjustable automatic backups and point-in-time-restore for up to 35 days.
- Enterprise-grade security and compliance to protect sensitive data at-rest and in-motion.
- Security covers data encryption on disk and SSL encryption between client and server communication.
- Built-in high availability with no additional cost (99.99% SLA)
- Predictable performance and inclusive, pay-as-you-go pricing
- Vertical scale as needed, within seconds
- Monitoring and alerting to assess your server
- Enterprise-grade security and compliance.
- Ability to protect sensitive dat at-rest and in-motion
- Automatic backups and point-in-time-restore for up to 35 days.
- Three pricing tiers: Basic, General Purpose, and Memory Optimized. Each offers different resource capabilities to support your db workloads. You can build your first app on a small db for a few > dollars a month, and then scale to meet your needs.
- Horizontally scales queries across multiple machines by using sharding.
- Its query engine parallelizes incoming SQL queries across these servers for faster responses on large datasets.
- Serves applications that require greater scale and performance, generally workloads.
- Apps built for PostgreSQL can run distributed queries on Hyperscale (Citus) with standard connection libraries and minimal changes.
- Platform as a Service (PaaS) db engine
- 99.99% uptime SLA
- Automated backups and configurable backup retention period
- Many of the same features as Azure SQL DB, but offers several options that might no be available on Azure SQL DB.
- Migrate on-prem data from an SQL Server to the cloud using the Azure DB Migration Service (DMS) or native backup and restore.
- Make sure there are no blocking issues when migrating.
- Once any issues are resolved, you can migrate the data, then cutover from the on-prem SQL Server to the Azure SQL Managed Instance by changing the connection string in your apps.
- Discover
- Assess
- Migrate
- Cutover
- Optimize
Azure Synapse Analytics
- Formerly 'Azure SQL Data Warehouse'
- A limitless analytics service that brings together enterprise data warehousing and big data analytics.
- Data can be queried on your terms by using either serverless or provisioned resources at scale.
- Brings a unified experience to ingest, prepare, manage, and serve data for immediate BL and ML needs.
Azure HDInsight
- Fully managed, open-source analytics service for enterprises.
- Makes it easier, faster and more cost-effective to process massive amounts of data.
- Can run popular open-source frameworks and create cluster types such as:
- Apache Spark
- Apache Hadoop
- Apache Kafka
- Apache Storm
- Machine Learning Services
- Supports a broad range of scenarios such as:
- Extraction, transformation, and loading (ETL)
- Data Warehousing
- Machine Learning
- IoT
Azure Databricks
- Unlocks insights from all of your data and helps build AI solutions.
- Can set up Apache Spark env in minutes, and autoscale/collaborate on shared projects in an interactive workspace.
- Supports:
- Python
- Scala
- R
- Java
- SQL
- TensorFlow
- PyTorch
- Scikit-learn
Azure Data Lake Analytics
- On-demand analytics job service that simplifies big data.
- Instead of deploying, configuring, and tuning hardware, you write queries to transform your data and extract valuable insights.
- The analytics service can handle jobs of any scale instantly by setting the dial for how much power you need.
- You only pay for your job when it is running, making it more cost-effective.