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Category: Cloud

Date and Time Functions in Cosmos DB

Published 2020-11-04 by Kevin Feasel

Hasan Savran walks us through date and time functions in Azure Cosmos DB:

Json does not have datetime data type, you need to keep the datetime information in string. This can be a problem for database engines specially if user needs to search by date or sort by date. Cosmos DB team introduced bunch of datetime functions to the Azure Cosmos DB database engine this month. You can read my older post about DateTime in CosmosDB if you like to know how Azure CosmosDB saves the datetime in documents. I will cover the new datetime functions in this post. Here is the list of the functions 

Click through for those functions and how you can use them.

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Geospatial Analysis with Azure Data Explorer

Published 2020-11-04 by Kevin Feasel

Chris Webb continues along a theme:

Since last week’s blog post about dynamic M parameters generated so much interest, this week I thought I’d give you another example of something cool you can do with them when you’re using Azure Data Explorer (ADX) as a DirectQuery source in Power BI: geospatial analysis.

Let’s say you work for a chain of supermarkets and want to use Power BI see what other competing stores are close to one of your stores.

Read on for the rest of the story.

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SQL Server Installation Options for Testing Azure DevOps Deployments

Published 2020-11-02 by Kevin Feasel

Kevin Chant looks at the different options available when trying to set up local testing of SQL Server databases using Azure DevOps deployments:

One way you can work around the above scenario is to install multiple virtual machines. Now the first thing you might realize is that this will also take up a lot of compute and storage.

In reality, I use to use this method myself in the past using Hyper-V. To reduce the amount of storage the virtual machines used in Hyper-V I use to used parenting disks.

Since the introduction of containers and Docker this has become a less popular option. However, you can still read an old post of mine with tips in here.

Click through for additional options.

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Azure Elastic Queries, Jobs, and Transactions

Published 2020-10-22 by Kevin Feasel

Steve Hughes walks us through three Elastic concepts in Azure:

Elastic queries allow developers to interact with data from multiple databases supported on the Azure SQL database platform including Synapse. Elastic queries are often referred to as Polybase which is currently implemented in SQL Server 2019 and Azure Synapse. The key difference is that elastic queries only allow you to interact with other Azure SQL Databases but not Hadoop or other database implementations (e.g. Teradata or Oracle). Part of the confusion comes from the fact that the implementation looks very similar. Both toolsets use external tables in SQL Server to interact with the connected data sources. However, Polybase requires additional components to run whereas elastic queries are ready to go without additional setup.

Read on for more information, including demos.

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Tips for Using Azure Table Storage

Published 2020-10-22 by Kevin Feasel

Adrian Hills takes us through using Azure Table Storage:

Azure Table Storage is a NoSQL key-value PaaS data store that can be a great option for highly scalable, highly available systems. It supports storing petabytes of data and a flexible data schema, meaning different entities in the same table can have different schemas. References to NoSQL databases having “flexible schema” or being “schema-less” can give the impression that database schema design is a thing of the past and that you can bypass it and focus more on the application code. The reality is, even in this NoSQL world, schema design is very important and if you don’t give it due care and attention, then it can come back to bite you.

If you have a RDBMS background and are new to Azure Table Storage, it’s common to find yourself “thinking in SQL” and trying to solve database modeling requirements with a SQL approach before then trying to translate that to a key-value mindset. In this blog post, I’ll cover some of the fundamentals of Azure Table Storage and dive into some common questions you might find yourself asking about Azure Table Storage. Where code samples or references are applicable in this blog post, we’ll be focusing on .NET and using the Azure SDK (specifically relating to the Microsoft.Azure.Cosmos.Table nuget package).

Read on for the full story.

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Self-Service with Azure Synapse Analytics

Published 2020-10-21 by Kevin Feasel

Paul Andrew lays out an interesting idea:

I’ve been playing around with Azure Synapse Analytics for a while now exploring the preview features and trying to find a meaningful use case for the ‘single pane of glass’ capabilities. In this post I’m exploring one possible option/idea for creating a very simple self service approach to dataset ingestion and consumption. Full disclosure, the below is far from technical perfection for lots of reasons, I mainly wanted to put something out there as an idea and use it to maybe start a conversation.

Click through to see Paul’s take on the matter.

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The Raw Facts on Azure SQL DB Serverless

Published 2020-10-21 by Kevin Feasel

Taiob Ali gives us a briefing summary on Azure SQL Database Serverless:

Occasionally, load balancing automatically occurs if the machine cannot satisfy resource demand within a few minutes. For example, if the resource demand is 4 vCores, but only 2 vCores are available, it may take up to a few minutes to load balance before 4 vCores are provided. The database remains online during load balancing except for a brief period at the end of the operation when connections are dropped.

Click through for more points along these lines.

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