5X vs Fabric

Microsoft Fabric sounds good on paper but when it comes down to it, there is a lot to be desired.
Last updated:
September 25, 2024
August 16, 2024
Krishnapriya Agarwal

Krishnapriya Agarwal

Content Marketing Manager

Microsoft Fabric is the evolution of Azure’s core data services, combining Azure Data Factory, Azure Synapse, One Lake, and Power BI into one integrated offering. Fabric brings together these services to streamline data workflows and simplify integration.

However, this integration doesn’t necessarily equate to maturity or completeness across the data readiness spectrum.


The true measure of a data platform is not just in AI capabilities, query speed, or storage capacity but in data readiness. Clean, structured, and centrally modeled data serves as the foundation for business intelligence, advanced analytics, data activation, and AI. Without clean and accessible data, even the most advanced AI models are limited by their inputs. The five key layers of a data-ready system are:

The five layers of a data-ready system are:

  1. Ingestion
  2. Warehouse
  3. Modeling
  4. Orchestration
  5. Business Intelligence

How does Fabric measure up against these layers of a data readiness platform? Let's find out.

Microsoft Fabric

Azure architecture diagram

25%

Ingestion

  • Uses Azure Data Factory to create ingestion pipelines
  • Supports connectors for databases, files, and SaaS applications
  • Falls short in handling complex data pipelines and lacks robust real-time processing capabilities compared to specialized streaming platforms
  • Incorporates Azure Event Hubs for real-time data ingestion, better suited for streaming rather than batch processing
  • Relies on Azure Stream Analytics for real-time analytics, which is limited by its less comprehensive data transformation capabilities
70%

Warehouse

  • Azure Synapse Analytics combines data warehousing and data lake capabilities. Supports SQL-based analytics and Spark for big data processing. Offers dedicated SQL pools for high-performance data warehousing.
  • Azure SQL Database for relational database needs, often used as a data mart.
  • Heavy reliance on Azure infrastructure can restrict flexibility and increase costs.
  • Doesn’t match the performance of dedicated data warehouses for complex OLAP workloads.
50%

Modeling

  • Supports SQL, Python, and Scala for data manipulation and analysis. Offers MLlib for ML algorithms.
  • Azure Synapse Analytics provides data modeling through SQL views and stored procedures.
  • Lacks out-of-the-box table and column-level data lineage.
  • Uses Spark SQL for complex transformation and processing, and DataFrames for manipulation.
  • Lacks an enterprise-grade modeling tool like dbt natively.
40%

Orchestration

  • Offers Azure Data Factory to orchestrate data pipelines, schedule workflows, and manage dependencies.
  • Provides Azure Logic Apps for building cloud-based application workflows with connectors to various services.
  • More complicated to manage (schedule and orchestrate) data pipelines as it uses multiple tools.
  • Struggles with complex, dynamic, or branching workflows.
80%

Business Intelligence

  • Offers integrations with Power BI and Power BI Embedded.
  • Lacks integrations with other popular BI tools like Tableau, Looker, Sigma, etc.

How 5X complements Fabric

100%

Ingestion

  • Offers 500+ pre-built connectors from all of the most used data sources.
  • Hours, day implementations for custom connector development for the long tail of connectors.
  • Simplifies handling incremental data updates for scenarios requiring near real-time data pipelines.
  • Support for Apache Iceberg Tables in S3 or other flat storage.
100%

Warehouse

  • Works with multiple cloud warehouses like GBQ, Snowflake, Redshift, and Databricks.
100%

Modeling

  • Integrates with dbt for enterprise-grade data modeling.
  • Offers features like lineage tracking, version control, and modular transformations.
  • Supports SQL, Python, and notebooks for transformation flexibility.
  • Offers table and column-level data lineage.
100%

Orchestration

  • Offers Dagster to ship pipelines quickly with 1-click scheduling.
  • Enterprise grade scheduling and DAGS with easy-to-use UI.
  • Prebuilt templates to accelerate dev time.
  • Easier to manage pipelines in a unified workspace.
100%

Business intelligence

  • Compatible with any BI tool.
  • Provides 5X BI as an inbuilt option in the platform.
  • Deep integrations and provisioning of Power BI, Looker, Sigma and Tableau from 5X.

Fabric vs 5X: A comparison on core data readiness

Feature

Fabric

5X

Warehouse
  • Offers Azure Synapse Analytics for integrated warehousing.
  • Supports data lakes with Azure Data Lake Storage (ADLS).
  • Offers native integration with SQL Data Warehouse.
  • Can be costly for large-scale deployments.
  • Integration issues with non-Microsoft tools.
  • Works on top of multiple cloud warehouses like Databricks, GBQ, Redshift, and Snowflake for storage flexibility.
Ingestion
  • ADF native connectors can be used for data ingestion and transformation in Synapse pipeline.
  • Supports custom connector development with Azure Logic Apps and Azure Functions.
  • Real-time ingestion with Azure Event Hubs and Azure IoT Hub.
  • Vast library of pre-built connectors for various data sources (databases, cloud storage, SaaS applications) offer out-of-the-box integrations with common data sources
  • Supports custom connector development for niche sources or data transformations during ingestion. This allows for tailored data acquisition from non-standard APIs or formats.
  • Offers support for Apache Iceberg Tables.
Modeling
  • Limited support for enterprise-grade modeling through Azure Data Factory.
  • Supported languages include Python, Scala, SQL and .net
  • Can be challenging to scale in large deployments
  • Supports Git integration for version control.
  • Lacks enterprise-grade modeler like dbt
  • Offers enterprise-grade modeling
  • Supports SQL, Python notebooks for transformation flexibility, offering a wider range of options compared to Fabric.
  • Native support for notebooks for analyst productivity.
  • Connection to GitHub enables collaboration and version control.
Orchestration
  • Provides orchestration with Azure Data Factory, but lacks the advanced features of enterprise-grade orchestrators.
  • Offers Spark pools to run distributed data processing and ML workloads using Apache Spark.
  • Supports Azure Logic Apps and Azure Functions for custom workflows.
  • Basic scheduling and trigger-based orchestration available.
  • Doesn’t offer an enterprise-grade orchestrator.
  • Offers commercial-grade orchestrator for rapid pipeline deployment (one-click scheduling, pre-built templates)
  • Scheduling based on cron timings or event triggers.
  • Set up preferences for your Slack channel and emails to run alerts and notify the added sources.
Business Intelligence
  • Integrates with Power BI and Power BI Embedded.
  • Other products include Azure Analysis Services and Azure Synapse Analytics.
  • Doesn’t offer integration with other popular BI tools like Looker, Sigma, and Tableau.
  • Provides 5X BI as an in-built option in the platform.
  • Offers deep integrations and provisioning of Power BI, Looker, Sigma, and Tableau directly from 5X.
  • Quicker deployment and implementation for faster time-to-value for BI initiatives.

Other considerations

Connectivity

Fabric

Azure Data Factory has roughly 100 connectors and you still need to maintain pipelines, so it's not fully automated.


5X

5X Ingestion has over 600 connectors out of the box and we're able to build custom connectors for you in hours instead of weeks.

Vendor lock-in

Fabric

Fabric, being Azure-based, has a massive vendor lock-in. This is all Microsoft based and if you move to other popular warehouses like Snowflake everything needs to be rebuilt.


5X

5X works on top of multiple data warehouses like Snowflake, Fabric, Big Query, and Redshift, and relies on multiple open source technologies like dbt, Dragster, Superset. This means that you can reuse your transformations on 5X if you ever decide to leave.

Use case

While Fabric is more suitable for BI-focused workloads and data analysts, 5X caters to both data engineers and analysts.

Skill transferability

Fabric

Fabric relies on proprietary languages (DAX, Power Query M, T-SQL with traditional SQL and Python) that are less intuitive, have a steeper learning curve, and aren't transferable outside the Microsoft ecosystem.


5X

5X uses widely-applicable languages like SQL and Python. Given this the learning curve on 5X is extremely easy and data engineers are able to use this with minimal specialized training.

Integrated services

Fabric

Fabric offers a comprehensive suite of services, including compute, storage, networking, analytics, and AI. However, Fabric requires expertise for implementation and optimization, which can incur massive additional costs to maintain an team of external consultants.


5X

5X’s integrated services are approximately 25% of the cost of US-based consultancies. This gives you a single point of contact across both the platform + services.

Support and documentation

Fabric

Microsoft's documentation for Fabric is often lacking, and the tools can be unintuitive, leading to slow and frustrating iteration cycles.


5X

5X's component tools have excellent documentation and community support.

Wrapping up

While Microsoft Fabric provides a rebranded and integrated data experience leveraging Azure’s existing tools, it falls short in key areas of data readiness, such as ingestion, modeling, and orchestration. 5X addresses these gaps by combining best-in-class tools that are flexible, proven, and tailored to diverse data workflows.

To address these gaps and solidify your data readiness, use 5X with Azure. Using 5X on top of Azure, you can build a scalable data platform that addresses the entire data lifecycle, from ingestion to consumption. This way, you can maximize the value of Azure's core strengths while overcoming its limitations in data readiness.

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