An Azure Data Explorer cluster is a pair of engine and data management clusters which uses several Azure resources such as Azure Linux VM’s and Storage. The applicable VMs, Azure Storage, Azure Networking and Azure Load balancer costs are billed directly to the customer subscription.
Azure Data Explorer clusters are billed on a per minute basis. Azure Data Explorer charges you for each VM in the cluster as well as Azure Data Explorer markup for some components of a cluster. Azure Data Explorer markup is proportional to the number of the VM vCores running in the engine cluster.
Pricing Details
Azure Data Explorer in now Generally Available and the Azure Data Explorer Markup price below reflects GA price.
Azure Data Explorer markup
COMPONENT | PRICE |
---|---|
Azure Data Explorer markup | ¥ 0.7/core per hour |
Developer Tier
Use the Developer tier to develop and test applications. The developer tier does not offer an SLA and should not be used for applications in production.
Instances | Number of cores | RAM | Pricing |
---|---|---|---|
D11 v2 | 2 | 80 GiB |
¥ 1.73/hour
( about ¥ 1,287.12/mouth ) |
Instances
Azure Data Explorer offers one types of instance families depending on your workload needs. Storage optimized instances are ideal for workloads that need fewer queries over a large volume of data.
Compute Optimized instances
Dv2 series
Instances | Number of cores | RAM | Pricing | Azure Data Explorer Markup | Pay In Advance total price |
---|---|---|---|---|---|
D11 v2 | 2 | 80GB SSD |
¥ 1.73/hour
( about ¥ 1,287.12/mouth ) |
¥ 1.4/hour
( about ¥ 1,041.6/mouth ) |
¥ 3.13/hour
( about ¥ 2,328.72/mouth ) |
D12 v2 | 4 | 160GB SSD |
¥ 3.46/hour
( about ¥ 2,574.24/mouth ) |
¥ 2.8/hour
( about ¥ 2,083.2/mouth ) |
¥ 6.26/hour
( about ¥ 4,657.44/mouth ) |
D13 v2 | 8 | 317B SSD |
¥ 6.92/hour
( about ¥ 5,148.48/mouth ) |
¥ 5.6/hour
( about ¥ 4,166.4/mouth ) |
¥ 12.52/hour
( about ¥9,314.88/mouth ) |
D14 v2 | 16 | 628GB SSD |
¥ 13.83/hour
( about ¥ 10,289.52/mouth ) |
¥ 11.2/hour
( about ¥ 8,332.8/mouth ) |
¥ 25.03/hour
( about ¥ 18,622.32/mouth ) |
Storage Optimized instances
DSv2 Series
Instances | Number of cores | RAM | Pricing | Azure Data Explorer Markup | Pay In Advance total price |
---|---|---|---|---|---|
DS13 v2 | 8 | 1 TB SSD |
¥8.00/hour
( about ¥ 5,952/mouth ) |
¥5.60/hour
( about ¥4,166.4/mouth ) |
¥13.60/hour
( about ¥ 10,118.4/mouth ) |
DS13 v2 | 8 | 2 TB SSD |
¥9.09/hour
( about ¥ 6,762.96/mouth ) |
¥5.60/hour
( about ¥ 4,166.4/mouth ) |
¥14.69/hour
( about ¥ 10,929.36/mouth ) |
DS14 v2 | 16 | 3 TB SSD |
¥17.08/hour
( about ¥12,707.52/mouth ) |
¥11.20/hour
( about ¥ 8,332.8/mouth ) |
¥28.28/hour
( about ¥ 21,040.32/mouth ) |
DS14 v2 | 16 | 4 TB SSD |
¥18.17/hour
( about ¥ 13,518.48/mouth ) |
¥11.20/hour
( about ¥ 8,332.8/mouth ) |
¥29.37/hour
( about ¥ 21,851.28/mouth ) |
Esv4 Series
Instances | Number of cores | RAM | Pricing | Azure Data Explorer Markup | Pay In Advance total price |
---|---|---|---|---|---|
E8s v4 | 8 | 1 TB SSD |
¥4.83/hour
( about ¥ 3,593.52/mouth ) |
¥5.60/hour
( about ¥4,166.4/mouth ) |
¥10.43/hour
( about ¥ 7,759.92/mouth ) |
E8s v4 | 8 | 2 TB SSD |
¥5.91/hour
( about ¥ 4,397.04/mouth ) |
¥5.60/hour
( about ¥4,166.4/mouth ) |
¥21.94/hour
( about ¥ 16,248.96/mouth ) |
E16s v4 | 16 | 3 TB SSD |
¥10.74/hour
( about ¥ 7,990.56/mouth ) |
¥11.20/hour
( about ¥ 8,332.8/mouth ) |
¥21.94/hour
( about ¥ 16,323.36/mouth ) |
E16s v4 | 16 | 4 TB SSD |
¥11.83/hour
( about ¥ 8,801.52/mouth ) |
¥11.20/hour
( about ¥ 8,332.8/mouth ) |
¥23.03/hour
( about ¥ 17,134.32/mouth ) |
FAQ
Expand All-
What is a Azure Data Explorer Markup?
We charge Azure Data Explorer Markup for fast data ingestion, caching, querying and manageability capability of Azure Data Explorer. The charge is directly proportional to the number of engine vCores in the Azure Data Explorer cluster.
-
How many nodes run as part of a Azure Data Explorer cluster?
You can choose to run as many engine nodes as you want. The number of engine nodes largely depends on how much data you ingest and your query performance requirements. You can also use Azure Data Explorer’s auto-scale function to dial up and dial down the number of engine nodes. The number and type of data management nodes are auto selected for you depending on your data ingestion needs. Click here to understand more about cluster type.
-
How does the billing work when cluster is stopped/paused?
When ADX Cluster is stopped/paused, all the compute resources are decommissioned. All the Storage artifacts are still preserved and once ADX cluster is started again, Compute is deployed with the same Storage artifacts. When the cluster is stopped, customers are only billed for underlying storage accounts. ADX Markup is only calculated on Engine compute resources and when cluster is stopped, ADX markup is not charged.
-
Could you give me an example on how billing works?
Azure Data Explorer clusters run engine nodes and data management nodes. Depending on your workload needs, you can choose the number of engine management nodes. The service auto selects the type and number of data management nodes. For your engine nodes, you will be billed for Azure VM costs as well as Azure Data Explorer Markup. For example, let’s say you run a Azure Data Explorer cluster for 100 hours in China East2. Let’s assume you choose 8 D13 v2 instances for engine nodes, and the service auto selects 2 D3 v2 instances for data management nodes. The billing would be the following:
Engine Nodes:
VM cost for 8 D13 v2 instances —100 hours x 8 instances x ¥6.92/hour = ¥5,536
Azure Data Explorer markup for 8 D13 v2 instances —100 hours x 8 instances x 8 vCores/instance x ¥0.7/vCore = ¥4,480
Data Management Nodes:
VM cost for 2 D3 v2 instances — 100 hours x 2 instances x ¥2.04/hour = ¥408
The total cost of running this Azure Data Explorer cluster for 100 hours would be: ¥10,424
Depending on your data retention policy, you will also incur networking and storage charges as a result of using Azure Data Explorer.
Support & SLA
If you have any questions or need help, please visit Azure Support and select self-help service or any other method to contact us for support.
To learn more about the details of our Service Level Agreement, please visit the Service Level Agreements page.