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Ozessa

We build and manage reliable data systems inside your Microsoft Fabric workspace. You own everything.

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Ozessa is a trading name of OZESSA LTD.
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Strategic Overview
Microsoft Fabric vs Google BigQuery: A 2026 TCO Analysis
Owned by you. Built for truth.

Microsoft Fabric vs Google BigQuery: A 2026 TCO Analysis

Evaluating the cost of compute versus the cost of integration.

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FABRICENGINE
ERP
CRM
API
SQL
IoT
XLS
DeploymentInside your Microsoft tenant
Data Ownership100% yours
Lock-inNone - you keep everything
Built on Microsoft FabricEnterprise-grade architecture
Operational Depth
TL;DR / Executive Summary

BigQuery excels at Serverless, on-demand SQL execution, but requires third-party automation tools.

Fabric provides a unified F-SKU capacity model that includes ingestion, transformation, and Power BI hosting.

For M365-native organizations, Fabric reduces Total Cost of Ownership (TCO) by eliminating integration overhead.

Read Time
16 MIN READ
Authority
Strategic Overview
Tier
Technical Evaluation
KEY FACTS
FACT_01

Fabric eliminates 100% of egress fees between data engineering and Power BI.

FACT_02

BigQuery on-demand pricing ($6.25 per TB scanned) scales linearly and unpredictably with ad-hoc queries.

FACT_03

Fabric OneLake supports direct Parquet/Delta ingestion without proprietary storage taxes.

Definition

What is Compute Capacity Modeling?

The process of forecasting the financial cost of a data platform by analyzing the reserved vs. on-demand execution requirements of the architecture.
Problem analysis
A. Symptom

Visible Signal

Surprise $10,000 monthly invoices from BigQuery due to unoptimized analyst queries.

B. Business Impact

Consequence

Financial unpredictability and restricted data access to control costs.

C. Hidden Failure

Architecture Flaw

Using a consumption-based pricing model without strict query governance.

Root cause

Google BigQuery separates storage and compute effectively, but its default consumption model penalizes poor SQL optimization. When a business analyst runs a SELECT * query on a Petabyte table, the business is billed directly for the scan. Microsoft Fabric\'s F-SKU model acts as a "Cell Phone Data Plan," providing reserved capacity that throttles rather than over-billing when limits are reached.

Our solution

The Reliability Engine Response

Our architecture mandates a reliability-first approach, injecting comprehensive markers and circuit breakers into the core transformation logic.

1

Cost-modeled migration from BigQuery to Microsoft Fabric.

2

Deployment of Fabric Capacity Metrics Apps for strict compute governance.

3

Translating BigQuery SQL dialects to Spark SQL and T-SQL.

Business impact
Zero-Integration Overhead
Time Recovered
30% Predictable TCO
Cost Mitigation
Runaway Query Billing
Risk Exposure
Native Power BI Integration
Metric Accuracy
Technical Analysis

For organizations evaluating Microsoft Fabric vs Google BigQuery, the decision hinges on predictability versus raw ad-hoc scale. BigQuery remains a powerhouse for unstructured, petabyte-scale machine learning. However, for SMEs reliant on Power BI, the integration tax of BigQuery is significant. You must pay for Google Cloud storage, pay for BigQuery compute scans, and then pay again for Power BI Premium licensing and network egress to visualize the data.

Microsoft Fabric consolidates this stack. A single Fabric F-SKU covers the Data Factory pipelines, the Spark compute for transformation, the OneLake storage layer, and the Power BI hosting. This unified architecture fundamentally changes the Data Strategy for mid-market CFOs seeking cost control.

Aleks - Lead Data Architect

Aleks

Lead Data Architect

Aleks is the Lead Data Architect at Ozessa, specializing in building mathematically verifiable data architectures on Microsoft Fabric. With a focus on long-term reliability and zero-lock-in data ownership, he engineers infrastructure that eliminates reporting risk.

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KEY TAKEAWAYS
  • ●Fabric provides cost predictability via F-SKUs.
  • ●BigQuery requires third-party BI and automation tools.
KEY DATA POINTS
Pricing Model: F-SKU Reserved Capacity
Integration: Native Power BI DirectLake
On this page
  • Executive Summary
  • Key Facts
  • Definition
  • Problem analysis
  • Root Cause
  • Our Solution
  • Business Impact
  • Technical Analysis
  • Key Takeaways
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DeploymentInside your Microsoft tenant
Data ownership100% yours
Lock-inNone - you keep everything
Built on Microsoft Fabric
Enterprise-grade architecture
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