Databricks pricing on Microsoft Azure: A Simple Guide

Databricks pricing on Microsoft Azure: A Simple Guide

Databricks pricing on Microsoft Azure

In this respect, databricks is a strong cloud data platform aimed at people who deal with machine learning, artificial intelligence, or data modeling. The Databricks Lakehouse combines the functionalities of a data lake and a data warehouse. This means that it is perfectly tailored for the development of complicated ML, AI, as well as other data analytics models. In addition, Databricks suggests that its lakehouse costs about 12 times less compared with traditional solutions. Is this a reasonable and accurate price for Databricks? Let’s look into it further below.

What is Azure Databricks?

The Databricks product is a cloud-based unified data analytics platform. This provides:

  • Scalable and secure setup for processing big data.
  • Machine learning analytics.
  • Visualizing data collaboratively through Microsoft Azure and Databricks joint efforts. Azure Databricks also comes with a managed cloud architecture with the ability to handle heavy loads of operations while providing users with a host of tools aimed at enabling their data science and engineering operations, such as shared working space for data exploration and testing. It also has an easy link with other Azure services that easily integrate Azure Databricks in existing systems and procedures.

Databricks pricing on Microsoft Azure is comprised of two tiers, which makes their feature sets differ to satisfy several workloads. The Azure Databricks offers a standard tier and a premium tier with varied operations for various workloads. When a customer creates an Azure Databricks workspace, they get to select the pricing tier. Nevertheless, after some time, they may also decide to go up to the other rate. The following is a comprehensive analysis of the pricing models.


Some of the benefits of Microsoft Azure include storage, networking, computing, analytics, and many more services as a cloud provider. The use of Azure services on-premises, hybrid, or in its public cloud. The cost per VM and DBU depends on the VM instance chosen by Azure Databricks. The processing capacity will be expressed in DBUs, while the charges are for utilization by second. DBU consumption depends on the type and size of the Azure Databricks instance.

Here is an illustration of the Central US region’s pricing:

  • All-purpose compute: Standard = $0.40 per DBU/hour, Premium = $0.55 per DBU/hour
  • Jobs compute: Standard = $0.15 per DBU/hour, Premium = $0.30 per DBU/hour
  • Light jobs compute: Standard = $0.07 per DBU/hour, Premium = $0.22 per DBU/hour
  • SQL compute: Premium = $0.22 per DBU/hour
  • SQL pro compute: Premium = $0.33 per DBU/hour
  • Serverless SQL: Premium = $0.42 per DBU/hour
  • Serverless real-time inference: Premium = $0.079 per DBU/hour

Pre-Purchased DBUs

While continuing to explore the cost of Azure Databricks, Pre-Purchased DBUs are one of the beneficial options in your investment. Savings with this plan can reach 37% as compared to the pay-as-you-go option. As a group of Databricks Commit Units (DBCUs) for a duration of one or three years, customers prepurchase DBUs. In order to create a single purchase based on the DBU usage across all tiers and workloads, a DBCU normalizes the customer’s Databricks usage.

The Central US region’s DBCU buy prices are as follows, highlighting the savings above on-demand pricing:

For a one-year DBU prepurchase plan:

  • 25,000 DCBUs: One-year plan = $23,500 (6% discount)
  • 50,000 DCBUs: One-year plan = $46,000 (8% discount)
  • 75,000 DCBUs: Three-year plan = $69,00 (8% discount)
  • 100,000 DCBUs: One-year plan = $89,500 (11% discount)
  • 150,000 DCBUs: Three-year plan = $135,000 (10% discount)
  • 200,000 DCBUs: Three-year plan = $172,500 (14% discount)
  • 300,000 DCBUs: One-year plan = $261,000 (13% discount)
  • 350,000 DCBUs: One-year plan = $287,000 (18% discount)
  • 500,000 DCBUs: One-year plan = $400,000 (20% discount)
  • 600,000 DCBUs: Three-year plan = $504,000 (16% discount)
  • 750,000 DCBUs: One-year plan = $577,500 (23% discount)
  • 1,000,000 DCBUs: One-year plan = $730,000 (27% discount)
  • 1,050,000 DCBUs: Three-year plan = $819,000 (22% discount)
  • 1,500,000 DCBUs: One-year plan = $1,050,000 (30% discount), Three-year plan = $1,140,000 (24% discount)
  • 2,000,000 DCBUs: One-year plan = $1,340,000 (33% discount)
  • 2,250,000 DCBUs: Three-year plan = $1,642,500 (27% discount)
  • 3,000,000 DCBUs: Three-year plan = $2,070,000 (31% discount)
  • 4,500,000 DCBUs: Three-year plan = $2,970,000 (34% discount)
  • 6,000,000 DCBUs: Three-year plan = $3,780,000 (37% discount)

How to optimize Azure Databricks Cost Optimization easily?

For big data processing and machine learning tasks, Azure Databricks can be a very useful tool, but it’s important to use the platform as cheaply as possible. Through this, you can define the needs of your company and choose between Azure Databricks’ Standard and Premium tiers. You may choose to enable autoscaling for Databricks clusters so that the number of worker nodes is adjusted automatically in accordance with workload. Autoscaling ensures that the resources are not over-provisioned and used only for the job at hand. Set up a policy for cluster shutdown to close the clusters after a given period of idleness. Therefore, since cluster resources are not utilized when idle, there is no waste of money. Use spot instances of Azure for your Databricks clusters to trim your compute costs.

Azure’s spot instances are simply lower-priced versions of unused Azure resources; however, Azure may cancel them instantly. They work well in scenarios that require tests, developments, and fault tolerances. Furthermore, choose efficient data formats that contain in-built compression, like Parquet or Delta Lake, to reduce storage costs. Furthermore, store your data on cloud storage services such as Azure Data Lake Storage or Blob Storage at affordable prices.

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