Data Lake Analytics pricing

An Azure Data Lake Analytics Unit or AU, is a unit of computation made available to your U-SQL job. Each AU gives your job access to a set of underlying resources like CPU and memory. Learn more about an AU

Increasing the number of AUs makes more compute resources available to your job. Depending on your job’s characteristics (e.g. how parallelisable it is, how much data it is processing etc.), you may see that your jobs run faster with more AUs. Azure Data Lake Tools for Visual Studio provides a number of tools that can help you diagnose the performance of your U-SQL jobs and estimate the optimal number of AUs. You can learn about how to use ADL Tools for Visual Studio here.

Price is determined by the number of AUs and job length. Let’s assume 2 cases:

• Case 1: A job takes 3 hours to complete with 10 AUs, so the price is calculated as 3*10=30 AU hours. If the job can take advantage of 20 AUs and runs twice as fast, the price would be 1.5*20= 30 AU hours. In this case the price is the same but latency is improved.
• Case 2: A job takes 5 hours to complete with 10 AUs, so the price is calculated as 5*10=50 AU hours. If the job takes 4 hours to complete when using 20 AUs, the price would be 4*20=80 AU hours. In this case, the total cost increased 80% with your job finishing one hour sooner.

Price is determined by the number of AUs you reserved for the month.

• A billing cycle is aligned to calendar month. Therefore, it always starts the 1st day of the month and ends the last day of the month.
• When you commit for the first time to a package, we will pro-rate the monthly price and AU-hours to the days left within that month. As an example if you commit to 1,000 AU-hours package and there are 10 days left within that month, you will immediately get 334 AU-hours (1,000 AU-hours / 30 days in a month x 10 days left) at a price of $- ($- / 31 days in a month x 10 days left). We pro-rate by 30 days for the AU-hours in a package and by 31 days for the price to make sure that the pro-rata is always in your favour.
• Units in a package reset the 1st day of the month. As an example, if you commit to 100 AU-hours and you have 20 AU-hours left by the end of the month, your package will be reset to 100 AU-hours the day after. There is no roll-over for unused AU-hours.
• You can choose a new package at any time. The change will be effective the first day of the next calendar month. This means that during a month if you have a package of 100 AU-hours and decide to commit to a 500 AU-hours package, this change will apply on the 1st day of the next calendar month. For the current calendar month, you will remain on the 100 AU-hours package.
• We use “seconds” as the unit of measure your package consumption is realised.
• Once your package is consumed, you would be charged for the overage consumption at a rate of $-/AU-hour.

Consumption is determined by the number of AUs and job length. Job length is influenced by the number of AUs assigned to the job as well as the characteristic of the job such as data size and computation complexity.

• Case 1: You committed to 100 AU-hours and submit a job that takes 2 hours and 30 minutes to complete with 1 AU, so the consumption is calculated as 2.5*1=2.5 AU Hours. You will have 97.5 AU-hours left in your commitment.
• Case 2: You committed to 100 AU-hours and have only 1 AU-hour left. You submit a job that takes 2 hours to complete with 2 AUs, so the consumption is calculated as 2*2=4 AU Hours. You will use your remaining AU hour and be charged 3 additional AU hours at the overage rate (1.5*3 = $-)

Azure Data Lake Analytics allows you to read and write data from Azure Data Lake Store, Azure Blob Storage and Azure SQL Database. The use of these services by Azure Data Lake Analytics can incur standard charges from these services (e.g., transactions, outbound data transfers, etc.). Please refer to the service pricing page for these services for more details.