Microsoft Fabric
Microsoft Fabric (formerly Azure Synapse) is Microsoft's unified analytics service, tightly integrated with Power BI, Azure Data Lake, and the Microsoft 365 ecosystem. It combines a SQL-based warehouse, a Spark-based lakehouse, and data integration pipelines in a single platform. Teams already invested in Azure and Power BI use Fabric to centralize GTM data, but its complexity and frequent rebranding create a steeper learning curve than Snowflake or BigQuery.
Why it ranks here
- Deep integration with Power BI, Excel, and Microsoft 365 makes it the natural choice for organizations standardized on the Microsoft stack.
- OneLake (unified data lake) stores data once and exposes it to SQL, Spark, and Power BI without duplication.
- Fabric Capacity pricing (pay for compute and storage together) simplifies budgeting for predictable workloads.
Where it sits
- Snowflake has a larger third-party ecosystem and simpler pricing; Fabric's capacity units are harder to forecast.
- BigQuery is easier to adopt for GCP-centric teams and has clearer per-query pricing.
- Databricks offers more mature Spark and ML tooling; Fabric's Spark integration is improving but lags behind.
How GTM Systems teams use it
- Load Salesforce and Dynamics 365 data into Fabric Lakehouse, transform it with Spark notebooks or T-SQL, then expose curated datasets to Power BI for executive dashboards.
- Use Data Factory pipelines (integrated into Fabric) to orchestrate ingestion from SaaS tools, apply transformations, and refresh Power BI datasets on a schedule.
- Build customer 360 views by joining CRM, ERP, and marketing data in Fabric Warehouse (SQL-based), then surface them in Power BI reports with row-level security.
- Query OneLake data with Spark (Python/Scala) for ML use cases or T-SQL for standard BI; both engines read the same Delta tables.
In-depth notes
- Capacity Unit pricing: pay for a pool of compute and storage. Overage charges apply if usage exceeds capacity.
- OneLake stores data in Delta format; you can query it with Fabric SQL, Spark, or external tools (Databricks, Trino) via Delta Sharing.
- Fabric rebranded from Azure Synapse Analytics in 2023; documentation and tooling are still catching up. Expect some rough edges.
- Power BI Premium is bundled into Fabric; teams already paying for Power BI Premium can shift to Fabric Capacity without added cost.
- Fabric's DirectLake mode lets Power BI query Delta tables in OneLake without importing data, cutting refresh times and storage duplication.
Best for
Azure-native organizations with heavy Power BI usage and a Microsoft 365 footprint; natural fit for teams migrating from on-premise SQL Server.
Avoid if
You run a multi-cloud stack or prefer best-of-breed tools over a unified platform. Snowflake or BigQuery will integrate more cleanly with third-party tools.
The rest of Data warehouse & modeling
Snowflake Leader Cloud data warehouse with compute-separate-from-storage architecture; dominant choice for GTM analytics and cross-system reporting. #2 
Google BigQuery Leader Serverless cloud data warehouse on GCP; pay-per-query pricing and tight integration with Google Analytics and Sheets. #3 
dbt (data build tool) Leader SQL-based transformation framework; turns raw warehouse tables into tested, version-controlled models using Jinja-templated SELECT statements. #4 
Databricks Strong Unified lakehouse platform combining data warehousing, streaming, and ML; built on Apache Spark and Delta Lake. #5 
ClickHouse Situational Open-source columnar database optimized for real-time analytics; extremely fast for aggregations on high-volume event data. #8 SQLMesh Situational Data transformation framework focused on incremental builds, fast CI, and column-level lineage; positioned as a next-generation dbt alternative. #9 
Coalesce Situational Visual data transformation platform built on Snowflake; provides a drag-and-drop DAG builder that compiles to dbt-compatible SQL. #10 
MotherDuck Situational Serverless cloud service for DuckDB; combines local query execution with cloud-based collaboration and storage. #11 
Firebolt Niche Cloud data warehouse optimized for sub-second query latency on large datasets; uses sparse indexing and aggressive caching. Learning guide
Setup
Sign up for a Fabric trial (60 days), create a workspace, and add a Lakehouse or Warehouse. Load sample data from Dynamics 365 or upload CSV files to OneLake, then query it with T-SQL in the Warehouse or Spark notebooks in the Lakehouse.
First thing to build
Create a dimension table from Salesforce Account data using CREATE TABLE in Fabric Warehouse (T-SQL syntax). Query it from Power BI Desktop using DirectLake mode to verify zero-copy access to OneLake.
What actually matters
- Capacity Units: purchase capacity in F-SKU tiers (F2, F4, F8) based on workload; overage charges apply if compute exceeds provisioned capacity.
- OneLake shortcuts: link external data (S3, ADLS, Dataverse) into OneLake without copying; query it alongside native Fabric tables.
- Power BI Premium migration: existing Power BI Premium licenses convert to Fabric Capacity; no added cost to adopt Fabric if you already pay for Premium.
- DirectLake vs Import: use DirectLake mode to query Delta tables in OneLake without importing data into Power BI; cuts refresh times and storage duplication.
Watch out
Fabric documentation and UI change frequently due to active development; expect gaps and outdated screenshots in official docs as of 2026.