![]() ![]() The inactive pipeline – you’re paying a small account for pipelines (about 40 cents currently). When you go through these, it depends on what the compute needs are to invoke the process (how much CPU, how much RAM, how much attempt storage you need).Ĥ. ![]() SSIS integration run times – here you’re using A-series and D-series compute levels. This is good to look at and do some comparisons since how many DMUs you’re using is where the bulk of your spend if going to be.ģ. You’re using 4X the DMUs but it’s happening in a quarter of the time. The other option is you could use 8 DMUs and it takes 15 minutes, this price is going to end up the same. Let’s say you specify and use 2 DMUs and it takes an hour to move that data. This is one you should be aware of as this will default to auto, which is basically using all the DMUs it can use and this is paid for by the hour. Volume of data moved – this is measured in DMUs (data movement units). ![]() With self-hosted, you want to copy activity moving from an on premises SQL Server to an Azure Blob Storage, a stored procedure to an Azure Blob Storage or a stored procedure activity running a stored procedure on an on premises SQL Server.Ģ. For the Azure activity runs it’s about copying activity, so you’re moving data from an Azure Blob to an Azure SQL database or Hive activity running high script on an Azure HDInsight cluster. Azure activity runs vs self-hosted activity runs - there are different pricing models for these. I hope that by pointing these out, you can gain an understanding of not only how it works, but how you can keep an eye on your spending.ġ. The pricing is broken down into four ways that you’re paying for this service. In today’s post I’d like to discuss how Azure Data Factory pricing works with the Version 2 model which was just released. ![]()
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