Azure SQL Database Service Tiers

Azure SQL Database Service tiers and database options (as of 3/Jan/2015):

Service tier Target workloads Transactional Perf. Objective SLA
Basic Best suited for a small size database, supporting typically one single active operation at a given time. Examples include databases used for development or testing, or small scale infrequently used applications. Reliability per hour 99.99%
Standard The go-to option for most cloud applications, supporting multiple concurrent queries. Examples include workgroup or web applications. Reliability per minute 99.99%
Premium Designed for high transactional volume, supporting a large number of concurrent users and requiring the highest level of business continuity capabilities. Examples are databases supporting mission critical applications. Reliability per second 99.99%


The following table shows the differences of the business continuity features across the service tiers:

BCDR option Basic tier Standard tier Premium tier
Point In Time Restore Any restore point within 7 days Any restore point within 14 days Any restore point within 35 days
Geo-Restore ERT < 12h 
RPO < 1h		 ERT < 12h 
RPO < 1h		 ERT < 12h 
RPO < 1h
Standard Geo-Replication Not included ERT < 30s 
RPO < 5s		 ERT < 30s 
RPO < 5s
Active Geo-Replication Not included Not included ERT < 30s 
RPO < 5s

Description of the terms:
• Disaster recovery (DR): a process of restoring the normal business function of the application
• Point in time restore: the ability to restore the database to a point in time in the past (within the backup retention period) in order to recover from data corruption caused by a human mistake or programmatic error
• Estimated Recovery Time (ERT): The estimated duration for the database to be fully functional after a restore/failover request.
• Recovery Point Objective (RPO): The amount of most recent data changes (time interval) the application could lose after recovery.

How is Standard Geo-replication different from Active Geo-replication?
First of all, standard geo-replication is built on the same technology as active geo-replication but is optimized for applications that use geo-replication only to protect the application from regional failures. The following list shows how standard geo-replication is different from active geo-replication:
1.Only one secondary database can be created in a Microsoft defined  “DR paired” Azure region. The list of the DR pairs can be found here.
2.The secondary is visible in the master database but cannot be directly connected to until failover is completed (offline secondary).
3.The secondary database is charged at a discounted rate as it is not readable (offline).

As a result some scenarios you could enable using active geo-replication are not possible with the standard geo-replication. The following table summarizes this delta

Scenario Standard Geo-replication Active Geo-replication
Regional disaster Yes Yes
DR drill Yes Yes
Online application upgrade No Yes
Online application relocation No Yes
Read load balancing No Yes

Comments

Post a Comment

Popular posts from this blog

Maven Crash Course - Learn Power Query, Power Pivot & DAX in 15 Minutes

Image
In the Maven Crash Course " Learn Power Query, Power Pivot & DAX in 15 Minutes ", Chris Dutton walks through a hypothetical business case while showcasing the power of modern Excel tools like Power Query, Power Pivot and DAX. Power Query is used to extract, transform, and load data from external sources like SQL databases, PDF and CSV files. A relational model is created to join the tables without writing a single formula. Exploratory analysis is done using Power Pivot and Data Analysis Expressions (DAX). Data Analysis Expressions is the language that we can use to define new calculated columns and measures to enhance our Data Model instead of the traditional cell formulas that we'd typically use if our data was stored in worksheets. Pivot Charts and slicers are used to design a simple interactive report that the sales managers can use to analyze revenue trends and product performance.
Read more

"Data Prep & Exploratory Data Analysis" course by Maven Analytics

Image
The Maven Analytics course on " Data Prep & Exploratory Data Analysis " by Alice Zhao is a beginner-friendly introduction to machine learning with Python. It covers the key steps of the data science workflow, including: Gathering Data Scoping a Project Modeling Data Sharing Insights Cleaning Data Exploring Data Modeling Data  Sharing Insights The presentation deck which is available as a download crisply summarizes the essential details and is a great reference to keep going back to. The course is well-suited for aspiring data scientists looking to get hands-on experience with the data prep and EDA stages of the machine learning workflow using Python and Jupyter Notebook. 
Read more

Gartner Magic Quadrant for Strategic Cloud Platform Services

Image
Gartner defines strategic cloud platform services (SCPS) as standardized, automated, public cloud offerings integrating infrastructure services (e.g., computing, network and storage), platform services (e.g., application, data and value-added services such as AI/ML) and transformation services (resources to help customers adopt cloud-oriented IT delivery models). Image - Gartner Insights I found interesting from the Gartner Magic Quadrant for Strategic Cloud Platform Services report: The eight SCPS providers & global hyperscalers featured in this Magic Quadrant control over 97% of the total CIPS market. While AWS has maintained profitability and a leading global infrastructure as a service (IaaS) and platform as a service (PaaS) market share of over 42%, its growth rate relative to its key competitors slowed in 2023. Azure public cloud market share is 26%. GCP's overall market share stands at 11.5%. Oracle's strategy of positioning OCI as the top cloud for Oracle software i
Read more