Updated October 25, 2026
· ~2 min read
Every major vendor now sells one place for data engineering, warehousing, BI and AI. Microsoft Fabric does it with one capacity that every workload draws from. Amazon SageMaker Unified Studio (generally available since March 2025) puts one workspace and catalog over AWS's existing analytics services, with data in Apache Iceberg. Databricks and Snowflake each grew from one side of the problem toward the other.
They differ most in billing and in what they assume about the rest of your stack.
Fabric's single capacity is what makes it easy to buy, and it is also its main operational risk. A heavy Spark job and the CEO's dashboard draw from the same capacity units. When the capacity is saturated, Fabric smooths and then throttles, and everyone feels it. Teams that succeed with Fabric separate production reporting from data engineering onto different capacities, and watch the Capacity Metrics app as closely as they would a database.
Question 1 of 2
Where do your applications and source data live?
**Microsoft Fabric:** you already run Power BI and Microsoft 365, and want warehouse, lakehouse and reporting on one bill. Simple to buy; plan capacity carefully, because data jobs and report users share it. **SageMaker Unified Studio:** your data and applications are on AWS. You keep paying for the underlying services (Redshift, Athena, EMR, Glue, Bedrock) and gain one workspace, catalog and governance layer over them. **Databricks:** engineering-heavy teams doing data engineering and ML at scale, on any cloud. **Snowflake:** SQL-first teams that want the least administration, and data sharing between companies.
AWS Data Lakehouse Platform
A production data lakehouse on AWS (S3-backed data lake with Glue, Iceberg, Athena, and Redshift) structured for analytics, ML feature stores, and governed data sharing.
Reporting Modernization: SSRS, Power BI Premium and Fabric
SSRS has no new versions after SQL Server 2025 and Power BI Premium capacity is moving to Fabric F SKUs. We inventory what is actually used, size the right capacity or licences, and move reports to Power BI, Fabric or Amazon Quick Sight on the data you already have.
We work with startups and growing companies on AWS architecture decisions. Tell us about your situation and we will recommend the right approach.
As of October 25, 2026. Provided as is, for general information, and accurate to the best of our knowledge on the date shown. Not legal, compliance, tax, financial or other professional advice. Prices, limits and vendor services change; check current vendor documentation before relying on anything here. Terms of use.