Cohort 4Register
Platform Comparison

Databricks vs Microsoft Fabric: The Differences a Data Engineer Is Asked About, and Which to Learn First

Databricks is a data and AI platform built on Apache Spark and Delta Lake that runs on AWS, Azure and Google Cloud. Microsoft Fabric is Microsoft's software-as-a-service analytics platform: one product with OneLake storage and workloads from pipelines to Power BI. Both run Spark over Delta tables, and Fabric can read Azure Databricks tables in place. Here is the comparison, question by question.

By Durgesh Yadav — Senior Data Engineer @ 7-Eleven · Updated 5 Oct 2026. Preparation guidance, not a hiring guarantee.

Databricks or Microsoft Fabric: what is the difference, and which should a data engineer learn first?

Databricks is a Spark and Delta Lake platform that runs on AWS, Azure and Google Cloud. Microsoft Fabric is Microsoft's SaaS analytics platform, with OneLake storage and Power BI built in. Both run Spark over Delta tables, so learn SQL and PySpark first, then the platform your target employers name. On AWS or Google Cloud, Databricks is the native choice.

Databricks Interview Questions See the Data Engineering cohort

Guide

What To Learn And How To Practice

What is the difference between Databricks and Microsoft Fabric?

Databricks is a data and AI platform built around Apache Spark and Delta Lake. It runs on AWS, Azure and Google Cloud, connects to the storage and security in your own cloud account, and keeps tables in Delta format under Unity Catalog. Microsoft Fabric is Microsoft's software-as-a-service analytics platform: one product with workloads for pipelines, Spark, a SQL warehouse, real-time data and Power BI, all reading and writing one store, OneLake. The overlap is large. Both run Spark notebooks, both store tables in the open Delta format, and Fabric can mirror an Azure Databricks Unity Catalog so its tables appear in OneLake without a copy. The distinction interviewers want is ownership: Databricks is a platform you set up inside a cloud account, and Fabric is a service your company switches on inside its Microsoft tenant.

Databricks vs Microsoft Fabric: a platform in your cloud against a service in your Microsoft tenant
DimensionDatabricksMicrosoft Fabric
What it isA data and AI platform built on Spark and Delta LakeMicrosoft's SaaS analytics platform, with several workloads in one product
Where it runsAWS, Azure (as Azure Databricks) and Google CloudAs a service in your organisation's Microsoft tenant, run by Microsoft
Where the data livesYour cloud storage, usually as Delta tablesOneLake, built on Azure Data Lake Storage, with tables in Delta Parquet format
EnginesSpark in notebooks and jobs, plus SQL warehousesSpark, T-SQL, KQL for real-time data, and Power BI
GovernanceUnity CatalogOneLake catalog, with Microsoft Purview for protection
How it billsDBUs plus your cloud's compute and storage billsA Fabric capacity (an F SKU) billed through Azure, plus Power BI licences where needed
ReportingConnects to Power BI, Tableau and other BI toolsPower BI is built in; Direct Lake reads OneLake tables without importing a copy
Named in Indian data-engineer postings, 23 Aug to 27 Sep 202619.1% of 1,470Not counted: Fabric is not one of the report's 18 technologies

How is each one billed, in principle?

Databricks bills Databricks Units for the compute you run, and on classic compute your cloud provider bills the machines and storage underneath, so there are two lines to watch. Fabric is bought as capacity: an F SKU purchased through Azure and billed per second, or reserved for a year, and the workloads in the workspaces on that capacity draw from the same pool of capacity units. Power BI sits partly outside that: creating and sharing Power BI content still needs Pro or Premium Per User licences, and on capacities smaller than F64 every viewer needs one too. Prices change, and this page quotes none.

Databricks: DBUs, plus the cloud's own bills on classic compute; job clusters and autoscaling are the levers
Fabric: one capacity shared by the workloads in its workspaces; the size of the F SKU is the lever
Power BI in Fabric: Pro or PPU to create and share; viewers need one too below F64
Both: interviewers ask what drove the bill and what you changed to cut it

Which interview questions compare the two?

The comparison comes up in three forms: define the difference, pick one for a scenario, and explain how the two run together. Answers that name the mechanism do better than answers that name a winner.

Storage: Delta tables in your own cloud storage against OneLake, and how OneLake shortcuts read Amazon S3 or Azure Data Lake Storage without copying
Governance: Unity Catalog against the OneLake catalog and OneLake security roles
Spark: the same engine in both; cluster setup, runtime versions and helper utilities differ
Orchestration: Databricks jobs against Fabric Data Factory pipelines
Reporting: Power BI over a Databricks SQL warehouse against Direct Lake inside Fabric

Pick one: an insurer on Microsoft 365, a small data team and hundreds of Power BI report readers

Fabric is the natural first look: the reports already live in Power BI, the lakehouse and pipelines sit in the same workspaces, and one capacity covers the engineering work. Say what would change the answer: an existing Databricks estate, heavy machine learning, or data that lives on AWS.

Pick one: a product company on AWS with clickstream events and machine learning models

Databricks: it runs natively on AWS, Structured Streaming writes Delta tables, and the same tables serve notebooks, models and SQL. Fabric could read the S3 data through a shortcut, but the processing would sit outside the company's own cloud.

Explain how the two run together

Azure Databricks writes Delta tables governed by Unity Catalog. Fabric mirrors that catalog, so the same tables appear in OneLake through shortcuts without a copy, and Fabric workloads read them there. Inside Fabric, who can read those tables is governed by Fabric's own workspace and item permissions, so expect a follow-up question on access.

Which should you learn first in India?

Follow the cloud your target employers use. In PrepNPlaced's India Tech Hiring Report, the 1,470 data-engineer postings collected 23 August to 27 September 2026 named Azure in 35.7%, AWS in 29.0%, Google Cloud (GCP) in 16.1% and Databricks in 19.1%. The report did not count Fabric, so it gives no Fabric share, and this page does not guess one. If the postings you read are mixed, Databricks is the safer first platform because it runs on all three clouds; add Fabric next if you are aiming at Microsoft-stack employers. The cohort teaches Databricks and Delta Lake in its Big Data and Apache Spark module.

Azure services company or GCC: Azure Databricks next to Azure Data Factory, then Fabric's lakehouse and pipelines
AWS or Google Cloud employer: Databricks, which runs natively on both
Power BI analyst moving toward engineering: Fabric, where the lakehouse and the reports share a workspace
Either way: SQL, PySpark and Delta Lake basics first; they are the same on both platforms
Certifications: Microsoft DP-700 (Fabric Data Engineer Associate) or the Databricks Certified Data Engineer Associate, matched to the employer

Related Guides

Keep Preparing

Move between roadmaps, interview questions, and tools without losing your preparation thread.

Databricks vs Snowflake

The other platform comparison data engineering interviews ask about.

Read guide

Power BI vs Microsoft Fabric

How Power BI sits inside Fabric, and what changes for an analyst.

Read guide

Databricks Interview Questions

Delta Lake internals, cluster tuning and the lakehouse round.

Read guide

Azure Data Factory Interview Questions

The Azure pipeline tool whose concepts carry into Fabric Data Factory.

Read guide

PySpark Interview Questions

The DataFrame code that runs on both platforms.

Read guide

India Tech Hiring Report 2026

The 1,470 data-engineer postings behind the cloud and Databricks shares.

Read guide

Data Engineering Cohort (live, weekend)

Snowflake and Databricks taught live across two modules; 192 live hours, 3 projects on GitHub.

Read guide

Data Careers Hub

Return to the parent resource hub for the full preparation path.

Open hub

FAQ

Common Questions

Is Microsoft Fabric replacing Azure Databricks?

No. Azure Databricks remains an Azure service, and Microsoft documents ways for the two to work together: Fabric can mirror an Azure Databricks Unity Catalog into OneLake, and Azure Databricks can connect to OneLake through its Azure Data Lake Storage compatible APIs. Companies already on Azure Databricks are not forced to move, so an answer that explains how the two connect beats one that picks a side.

Can Fabric run PySpark like Databricks?

Yes. Fabric's Data Engineering workload provides Apache Spark with notebooks and scheduled Spark jobs, and its lakehouse tables are Delta tables, so most DataFrame code moves across with small changes. What differs is the platform around Spark: cluster settings, runtime versions, helper utilities and how jobs are scheduled.

Which certification should a data engineer take: DP-700 or the Databricks one?

The one your target employer's stack uses. Microsoft's DP-700 (Fabric Data Engineer Associate) expects SQL, PySpark and KQL across ingesting, transforming, securing and monitoring data in Fabric. The Databricks Certified Data Engineer Associate covers foundational data engineering tasks on Databricks. A project you can explain counts for more than either.

Which is cheaper, Databricks or Fabric?

It depends on the workload and on how well it is run, and both vendors publish and change their prices, so this page quotes none. The structural difference: Databricks bills DBUs plus, on classic compute, your cloud's own bills; Fabric bills a capacity that its workloads share, with Power BI licences on top where needed. Interviewers want to hear what you would size and what you would monitor.

Do Indian job postings ask for Fabric?

PrepNPlaced has no count to give. The India Tech Hiring Report measured 18 technologies and Fabric was not one of them. What it did measure, across 1,470 data-engineer postings from 23 August to 27 September 2026: Azure in 35.7% and Databricks in 19.1%. Read ten postings from the companies you want and count Fabric yourself.

Next Step

Turn The Guide Into Practice

Use PrepNPlaced tools to turn this learning path into resume proof, targeted practice, and interview-ready explanations.

Databricks Interview Questions