Azure Analytics Platforms

Tags intermediate guide azure cloud-platform

BenchBox supports Azure-native analytics platforms alongside multi-cloud options (Databricks, Snowflake).

Overview

Microsoft Azure offers multiple analytics platforms for different workload patterns:

Platform

Type

Focus Area

Status in BenchBox

Microsoft Fabric

Unified SaaS Platform

Data engineering, warehousing, BI, real-time analytics

Supported

Azure Synapse Analytics

Enterprise Data Warehouse

Data warehousing, big data analytics

Planned

Azure Data Explorer

Real-time Analytics Engine

Time-series, telemetry, streaming data

Under evaluation

Microsoft Fabric

Status: Supported (Warehouse items only)

Platform Type: Unified SaaS data analytics platform

Technical Characteristics:

  • OneLake data lake with multi-cloud support

  • Integrated workloads: Data Engineering, Data Factory, Data Science, Real-Time Intelligence, Data Warehouse, Databases

  • Capacity-based pricing model

  • Built-in Copilot AI assistance

  • Delta Lake Parquet format (not SQL Server native format)

Common use cases:

  • Organizations consolidating multiple data tools into unified platform

  • Teams requiring integrated data engineering, warehousing, and BI

  • Multi-cloud data lake architectures

  • Self-service BI with Power BI integration

BenchBox Integration:

  • Supports Fabric Warehouse items via T-SQL

  • Entra ID authentication (service principal, default credential, interactive)

  • OneLake staging for bulk data loading via COPY INTO

  • Automatic query translation from standard SQL

Important: Only Warehouse items are supported. Lakehouse requires Spark integration and is not currently implemented.

See Microsoft Fabric Platform Guide for detailed usage.

Azure Synapse Analytics

Platform Type: Enterprise data warehouse and big data analytics service

Technical Characteristics:

  • Dedicated SQL Pools (MPP architecture)

  • Serverless SQL pools (pay-per-query)

  • Apache Spark pools for big data processing

  • T-SQL dialect with SQL Server compatibility

  • PolyBase for external data access

  • Azure AD authentication support

Common use cases:

  • Enterprise data warehousing on Azure

  • Big data analytics with Spark

  • Data lake queries via serverless SQL

  • Azure-native analytics workloads

Architecture: PaaS with choice of serverless or dedicated compute resources

Integration Considerations: Azure AD authentication, PolyBase staging, T-SQL dialect differences, concurrency management

Azure Data Explorer (Kusto)

Platform Type: Fast analytics service for real-time data

Technical Characteristics:

  • Kusto Query Language (KQL) with T-SQL support

  • High-throughput ingestion (up to 12 Mbps per core)

  • Time-series analysis functions

  • Streaming data support

  • Integration with Azure Event Hubs, IoT Hub

Common use cases:

  • Real-time telemetry and log analytics

  • IoT data analysis

  • Time-series workloads

  • Application performance monitoring

Architecture: Fully managed service optimized for time-series and streaming data

Integration Considerations: KQL query translation, streaming ingestion patterns, time-series benchmark adaptations

Implementation Roadmap

BenchBox maintainers are evaluating Azure platform integration based on:

  1. Community demand - User requests and sponsorship interest

  2. Technical complexity - Authentication, staging, query dialect differences

  3. Coverage gaps - Completing multi-cloud platform matrix (AWS, GCP, Azure)

Priority ranking:

  1. Microsoft Fabric - Highest priority due to Microsoft’s strategic direction and comprehensive SaaS offering

  2. Azure Synapse Analytics - Medium-high priority for enterprise data warehouse benchmarking

  3. Azure Data Explorer - Medium priority for real-time/streaming use cases

Current Workarounds

While native Azure platform support is under development, Azure users can:

  • Use Databricks on Azure - Fully supported in BenchBox

  • Use Snowflake on Azure - Fully supported in BenchBox

  • Use DuckDB locally - For development and testing on Azure VMs

Contributing

If your organization requires Azure platform support, please:

  1. Open a GitHub issue describing your use case

  2. Specify which Azure platform(s) you need

  3. Share any technical requirements or constraints

  4. Consider sponsorship to accelerate development

See the future platforms page for technical integration details.