Databricks vs Microsoft Fabric

Updated November 2026 · AppBreakup editorial

Databricks

A lakehouse platform combining data engineering, SQL warehousing and machine learning on your cloud.

Paid

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Microsoft Fabric

Microsoft's SaaS analytics platform combining a data lake, warehouse, data engineering and Power BI.

Paid

Visit Microsoft Fabric Microsoft Fabric profile

The short answer

Databricks suits data engineering and ML teams that want Spark, SQL and model training on AWS, Azure or Google Cloud, with data kept in open formats in their own storage. Microsoft Fabric suits organisations on Azure and Power BI that want one SaaS analytics platform and one capacity bill. The biggest difference is cloud choice: Databricks is multi-cloud, Fabric runs only on Azure.

Databricks or Microsoft Fabric: our take

Both are lakehouse-style platforms, but they come from different directions. Databricks was founded by the creators of Apache Spark, and Spark-based data engineering is still its core, alongside Databricks SQL warehouses, collaborative notebooks, MLflow for machine learning and Unity Catalog for governance. Data stays in open formats such as Delta Lake and Parquet in your own cloud storage. Fabric brings several Microsoft services together on OneLake, a single tenant-wide data lake: Data Factory pipelines, Spark notebooks, a SQL warehouse, real-time analytics, operational databases and Power BI all work on the same copy of data, with Copilot help and governance through Microsoft Purview.

Billing works differently. Databricks is pay as you go in Databricks Units (DBUs) with no up-front cost, and on most clouds the provider bills the underlying virtual machines separately, which makes total cost hard to predict. Fabric sells capacity, a shared pool of compute units billed by the hour or reserved for one or three years at about a 41% discount, plus storage. Capacity sizing is hard to estimate up front, and some sharing still needs separate Power BI licences. Both offer a free trial; Fabric gives each user a trial capacity.

Databricks runs on AWS, Azure and Google Cloud, which matters for multi-cloud teams or anyone not on Microsoft. Fabric runs only on Azure, but puts reporting right next to the data through built-in Power BI. Databricks has a steeper learning curve and is more than a team that only needs dashboards requires.

Choose Databricks for heavy data engineering and machine learning, multi-cloud setups, or a strong preference for open formats in storage you control. Choose Fabric if your organisation already runs on Microsoft 365, Azure and Power BI and wants ingestion, warehousing and reporting under one bill.

Choose Databricks if…

Data engineering and ML teams that want SQL, Spark and model training on one platform
Data stays in open formats in your own cloud storage
Covers ETL, SQL analytics and machine learning in one place

Choose Microsoft Fabric if…

Organisations on Azure and Power BI that want one analytics platform and one bill
One data lake shared by warehouse, Spark, real-time and BI engines
Power BI built in, so reporting sits next to the data

What is Databricks?

Databricks is a data and AI platform built around the lakehouse idea: data stays in open formats such as Delta Lake and Parquet in your own cloud storage, and Databricks provides the compute and tools on top. It was founded by the creators of Apache Spark, and Spark-based data engineering remains its core, alongside Databricks SQL warehouses for BI, collaborative notebooks, MLflow for machine learning, and Unity Catalog for governance. It runs on AWS, Azure and Google Cloud, and is aimed at data engineering and data science teams in mid-sized and large organisations. Pricing is pay-as-you-go in Databricks Units (DBUs), a normalised measure of processing, and on most clouds you also pay the cloud provider separately for the underlying virtual machines. A free trial is available. It is more of a platform to learn than a plain SQL warehouse, which makes it heavier than needed for teams that only want dashboards.

What is Microsoft Fabric?

Microsoft Fabric is a cloud analytics platform that brings several Microsoft data services under one SaaS product. Everything sits on OneLake, a single tenant-wide data lake, and different engines work on the same copy of data: Data Factory pipelines for ingestion, Spark notebooks for data engineering and data science, a SQL data warehouse, real-time event analytics, operational databases, and Power BI for reports and dashboards. Copilot features help write queries, notebooks and reports in natural language, and governance builds on Microsoft Purview. Instead of paying per service, you buy Fabric capacity: a shared pool of compute units, billed pay-as-you-go by the hour or reserved for one or three years at a discount, plus storage; Power BI licences are still needed for some sharing scenarios. A free trial gives each user a trial capacity. It runs entirely in Azure and the browser. It suits organisations already on Microsoft 365, Azure and Power BI, while multi-cloud teams often prefer Snowflake or Databricks.

Side by side

Attribute	Databricks	Microsoft Fabric
Pricing	Paid	Paid
Open source	No	No
Self-hostable	No	No
Platforms	Web	Web
Best for	Data engineering and ML teams that want SQL, Spark and model training on one platform	Organisations on Azure and Power BI that want one analytics platform and one bill
Status	Active	Active

Verified facts, compared

Facts both apps publish, checked on each vendor's own site.

Fact	Databricks	Microsoft Fabric
Pricing model	Pay as you go, no up-front cost	Pay-as-you-go or reserved capacity
Free trial	Yes	Yes, per-user trial capacity