Skip to main content

Azure SQL DB Tiers - Improvments in hardware options

שלום לכולם

והיום על שיפורים בקונפיגורציות של

Azure SQL DB in v-Core mode
 
 


 



תחת v-Core mode יש 3 אפשרויות:
  • General Purpose
    • Provisioned
    • Server Less
  • Hyper Scale 
  • Business Critical
בכל אחד מאלו אפשר לקבוע את כמות ה CPU והכמות סטורג'
 
כאשר Hyper Scale זו טכנולוגיה אחרת ועליה נכתוב בפעם אחרת.
 
General Purpose vs Business Critical - ההבדל ביניהם הוא האם ה SSD הוא מקומי בתוך השרת או שזה סטורג' מרכזי.
 
בכל אחד משני אלו עד היום אפשר היה לבחור בין Gen4 & Gen 5
כאשר ההבדל ביניהם הוא זה:
 
Gen 4 CPUs are based on Intel E5-2673 v3 (Haswell) 2.4 GHz processors.
Gen 5 CPUs are based on Intel E5-2673 v4 (Broadwell) 2.3 GHz processors.  
 
עכשיו הוסיפו עוד 2 אפשרויות
  • M-Series
  • FSv2 Series
זה נהיה מורכב - שימו לב
תחת General Purpose אפשר לבחור רק  FSv2 בנוסף ל Gen4 \ Gen5

 
 
תחת Business Critical אפשר לבחור רק M בנוסף ל Gen4 \ Gen5  
 
על סידרה M, על הכוח שלה ועל היכולות שלה אפשר לקרוא פה
 
 

 
אכן זה נהיה מורכב אבל אם רוצים לתת אפשרות לשליטה זה המקום 
 

Comments

Popular posts from this blog

How to restore deleted Azure Synapse dedicated SQL pool

  Existing dedicated pool can be easily restored from Azure portal or PowerShell command, but for now deleted pool could be restored from PowerShell only! Example: # Connect to Azure with system-assigned managed identity $AzureContext = (Connect-AzAccount -Identity).context # set and store context $AzureContext = Set-AzContext -SubscriptionName $AzureContext.Subscription -DefaultProfile $AzureContext # $AzureContext = Set-AzContext -SubscriptionName $SubscriptionName -DefaultProfile $AzureContext $SubscriptionName="Databases" $ResourceGroupName="stg-rg-we" $ServerName="stg-synapse-we"   $DatabaseName="sql_we_2023_11_07_13_42" $NewDatabaseName="sql_dp_we_deleted" ######################################## $token = (Get-AzAccessToken -ResourceUrl https://database.windows.net).Token $SubscriptionId = "ce088f9e-1111111a3914b" $DedicatedPoolEndPoint = "stg-synapse-we.sql.azuresynapse.net" $DedicatedPoolName = $DatabaseNam...

The journey to the Lakehouse

A long time has passed since the last post, we have gone through a long and tedious journey to adapt what Azure offers us, to our needs. Our needs were simple, the Current Datawarehouse (SQL Server on VM inazure) served the BI. ML teams worked on GCP, we want to let both teams to work on Azure in a platform that will have the ability to scale and will not fail every 2 days. We checked: Snowflake on azure Synapse analytics GCP We decided to go for the full Azure product for the reasons: Migration time support costs Synapse as a platform contains many components, and the challenge was to find what fits  us as an organization and as a group. The knowledge of the people and their abilities influenced the plans. Here's what we planned and what we did: We start to put everything in the Data Lake in parquet or delta format, build on top of Azure ADLS gen 2. We had to move some data to T-SQL compatible platform, so this involves setting up a dedicated Synapse pool , which is a fully man...

From DBA to Data Engineer in Azure

I recently moved a role From being a DBA Manager, Who is responsible for the operational databases. I moved to manage the data engineering group. So what exactly is the difference between the two functions? DBA - Production Databases: SQL\ NoSQL- 24*7, powerful server on premise or on the cloud, managed or semi managed, security tasks, high performance is a target, multiregional, HA as top priority. Developers are using Microservices - so we have many applications many services and many many Databases. Many kinds of DB's like Cloud IAAS and PAAS. Secure and audit the data is must. The Clusters must have Uptime as long as we can achive. Data Modeling - is so important too. Challenges and Problems in the data bases systems Lots of DB’s Lots of creators / no standards Lots of Consumers (Query, tools, SLA) Raw data Lots of data resources Data silos In Data Engineering we have other challenges for example we have Data lake and Data Warehouses : Batch process. Stream Process. many data ...