Do you want to learn more about Cosmos DB for SQL Server Admins and Developers? In a recent webinar with consultant Mike Donnelly, he’ll give you a quick outline of Cosmos DB, Microsoft’s multi-model database service, and why to use it. Cosmos DB is:
Do you want to learn how databases in Azure are more than SQL Server? In a recent webinar, Steve Hughes, reviews Azure’s database offerings. If you go to the Microsoft Azure site and open the database bucket, you’ll see quite a few database offerings from Microsoft. This webinar will look at use cases and costs around these, as well as related functionality.
As data volumes continue to grow and we’re storing more data and more kinds of data, people are asking questions about how best to store all that data. One question we hear is, how do I know if I need Cosmos DB or a NoSQL solution?
In this post about Cosmos DB, I’d like to dive into what Requests Units are and what it means to work with them in Cosmos. A Request Unit, like all other units inside of Azure, compile things like CPU, memory and IOPS, so you have a unified pattern with which to work.
To continue with my topic of Cosmos DB, today I’ll discuss the data consistency models that are supported within the context of Cosmos DB. If you don’t already know, data consistency is the ability of the data to be read once it has been written. When choosing a consistency model, you want to take into consideration consistency, availability and latency.
Today I’d like to walk through the multi model database portion of Cosmos DB and explain what multi model means to you. Multi model database service means that your data can be stored a number of different ways. Currently, Cosmos DB stores 4 different types of data and it allows you to integrate with an API and build out a user experience around these database storage types.
Do you need the ability of global distribution of your data and wonder which database is the best for this? Today, I’d like to give you a comparison between Azure SQL Database and Cosmos Database for global distribution.