SQL Server on an Azure Virtual Machine
Using Infrastructure as a Service (IaaS) is useful for
any application solutions that require a quick migration to the cloud with
minimal changes. All the versions and editions of SQL Server are available and offer
100% compatibility with SQL Server, allowing you to host as many databases as
needed and executing cross-database transactions.
There are also other benefits that may get you to consider using IaaS
platform including:
- Configure and manage
high availability, disaster recovery, and patching for SQL Server easier
than on-premises machines
- Customized
environment with full administrative rights
- SQL Server instances
with up to 64 TB of storage and as many databases as needed
- Fully supports SQL
Server transactional replication, AlwaysOn Availability Groups,
Integration Services, Log Shipping to replicate data, and traditional SQL
Server backups
In addition, migrating to SQL Server on an Azure Virtual Machine may be
an option for legacy systems, where application and database need to coexist in
the same server.
Because of the simple nature of the migration, migrating to this target
platform is often referred to as "lift and shift".
Azure SQL Managed Instance
SQL Managed Instance is an ideal migration destination for
organizations seeking a low-effort solution to transfer large numbers of
on-premises SQL Server databases to Azure. With broad SQL Server compatibility
and network isolation, it simplifies the lift-and-shift process while providing
a secure and cost-effective solution. You can backup and restore on-premises
databases to SQL Managed Instance, which offers the same features as SQL
Database, along with support for larger database sizes (up to 8 TB) and SQL
Server features such as SQL Agent, cross-database querying, and replication.
Using Azure SQL Managed Instance brings about the following benefits:
- Isolated environment
(single-tenant service with VNET, dedicated compute and storage resources)
- Customer
configurable backup retention and recovery
- Database Advisor and
Log Analytics for advanced workload analysis
- Automatic database
tuning and maintenance for predictable performance
- Monitor,
troubleshoot, and manage at scale
- Azure portal
functionality for manual service provisioning and scaling
- Microsoft Entra
authentication, single sign-on support
- Adheres to same
compliance standards as Azure SQL Database
- Encryption of the
data in transit and rest with customer provided encryption keys
- No patching and
version upgrade overhead
Azure SQL Database
Azure SQL Database is fully managed and provides organizations with a
highly performing, reliable, and secure, general purpose relational database
engine in the cloud. There are deployment models within Azure SQL Database,
each providing different benefits:
- Single database
A single database has its own resources and is deployed to a logical
SQL Database server where it's managed. There are several tiers of performance,
each providing different levels of throughput, performance, storage, and cost.
- Elastic pools
Elastic pools provide organizations with a cost-effective way for
deploying and managing multiple databases with different workload
characteristics. Databases that belong to an elastic pool are deployed onto a
single SQL Database server, allowing for shared resource utilization among all
databases within the pool.
Both single databases and elastic pools can be purchased using either
the DTU-based purchasing model or the vCore-based purchasing model.
- DTU-based
purchasing model
A Database Throughput Unit (DTU) is a unit of performance calculated by
blending CPU, memory, data I/O and transaction log I/O. The higher the DTU, the
higher the performance level. The DTU Purchasing Model lets customers control
their budgets with per-hourly, fixed price billing.
- vCore-based
purchasing model
The vCore purchasing model enables customers to select a performance
level based on vCores and memory. This model allows compute to be scaled
independently of the storage at a more granular level. As an added benefit, the
vCore purchasing model allows organizations to license Azure SQL Databases with
the Azure Hybrid Use Benefit for SQL Server. This means customers with Active
Software Assurance (SA) coverage for SQL Server Enterprise and Standard Edition
core licenses can receive savings of up to 30%.
Using a single Azure SQL Database service will suit many business
requirements that have databases with predictable performance requirements and
it can bring about the following benefits:
- A SQL Server engine
compatibility and native virtual network (VNET) support
- Dynamic scalability
with no downtime
- Built-in intelligent
optimization, global scalability and availability, and advanced security
options
- Eliminates hardware
costs and reduces administrative costs
- Built-in fault
tolerance infrastructure capabilities, Azure SQL Database provides
features, such as automated backups, Point-In-Time Restore, geo-restore,
and active geo-replication to increase business continuity for
applications hosting data in Azure SQL Database
- Databases of up to 4
TB or larger databases that can be horizontally or vertically partitioned
using a scale-out pattern
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based Enterprise Data Warehouse
(EDW) that takes advantage of Massively Parallel Processing (MPP) to quickly
run complex queries across large amount of data. It's a distributed system
designed to provide analytics on large data. Migrating to Azure Synapse
Analytics requires some design changes to table schemas and code that aren't
difficult to understand but might take some time to implement. If your business
requires an enterprise-class data warehouse, the benefits are worth the effort.
However, if you don't need the power of Azure Synapse Analytics, it will be
more cost-effective to use Azure SQL Database or SQL Server on Virtual Machine.
Consider using Azure Synapse Analytics when you:
- Have one or more
terabytes of data
- Plan to run
analytics on large amounts of data
- Need the ability to
scale compute and storage
- Want to save on
costs by pausing compute resources when you don't need them.
Don't use Azure Synapse Analytics when your workloads have:
- High frequency reads
and writes
- Large numbers of
singleton select statements
- High volumes of
single row inserts
- Row-by-row
processing needs
- Incompatible formats
(JSON, XML)
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