5X vs Fabric
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:
- Ingestion
- Warehouse
- Modeling
- Orchestration
- Business Intelligence
How does Fabric measure up against these layers of a data readiness platform? Let's find out.
Microsoft Fabric
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
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.
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.
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.
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
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.
Warehouse
- Works with multiple cloud warehouses like GBQ, Snowflake, Redshift, and Databricks.
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.
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.
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
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.
Building a data platform doesn’t have to be hectic. Spending over four months and 20% dev time just to set up your data platform is ridiculous. Make 5X your data partner with faster setups, lower upfront costs, and 0% dev time. Let your data engineering team focus on actioning insights, not building infrastructure ;)
Book a free consultationHere are some next steps you can take:
- Want to see it in action? Request a free demo.
- Want more guidance on using Preset via 5X? Explore our Help Docs.
- Ready to consolidate your data pipeline? Chat with us now.
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