Databases can scale up when deployed on-premise. How about the migration to cloud databases ? What are some of the differences ?
This post tries to find those answers. On-premise database can scale only under constraints requiring hardware resources, manpower and costs That said on-premise database can work without internet access, provide high tps, keep the data and applications in house, and can store sensitive data.
Database servers such as SQL server have also become cloud ready and even provide mission critical cloud performance while lately they have been focusing on advanced analytics and rich visualizations. Higher end database servers that require say 64 cpus are often an on-premise only choice..
We don't talk about data warehouses in this section because they are different from databases. That said Azure SQL DB and DW both work in the cloud as relational stores.
Azure Data lake Analytics and Azure data lake store are non-relational and while they are hosted in the cloud, the corresponding on-premise analytics system is usually fulfilled by Hadoop.
Analytics include such things as Federated Query, Power BI, Azure machine learning, and Azure Data Factory
Sql Server on an Azure VM is considered as IaaS while virtualized databases in the cloud is considered PaaS. In the latter case, the Azure Cloud Services manage scale and resilience while allowing the application developers to focus on application and Data. Regardless of the choice, they use consistent tools for all the database options above.
Migrating database from single servers to Azure VMs is straightforward but MDMs and other databases that are company assets involve more chores.
#sqlexercise : https://goo.gl/Zz1yoV
This post tries to find those answers. On-premise database can scale only under constraints requiring hardware resources, manpower and costs That said on-premise database can work without internet access, provide high tps, keep the data and applications in house, and can store sensitive data.
Database servers such as SQL server have also become cloud ready and even provide mission critical cloud performance while lately they have been focusing on advanced analytics and rich visualizations. Higher end database servers that require say 64 cpus are often an on-premise only choice..
We don't talk about data warehouses in this section because they are different from databases. That said Azure SQL DB and DW both work in the cloud as relational stores.
Azure Data lake Analytics and Azure data lake store are non-relational and while they are hosted in the cloud, the corresponding on-premise analytics system is usually fulfilled by Hadoop.
Analytics include such things as Federated Query, Power BI, Azure machine learning, and Azure Data Factory
Sql Server on an Azure VM is considered as IaaS while virtualized databases in the cloud is considered PaaS. In the latter case, the Azure Cloud Services manage scale and resilience while allowing the application developers to focus on application and Data. Regardless of the choice, they use consistent tools for all the database options above.
Migrating database from single servers to Azure VMs is straightforward but MDMs and other databases that are company assets involve more chores.
#sqlexercise : https://goo.gl/Zz1yoV
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