Azure Synapse Analytics vs Microsoft Fabric
Introduction
Fabric is considered a potential successor to Azure Synapse, and it exhibits notable differences and enhancements in both architecture and capabilities.
In this blog post, we will delve into the distinctions between Microsoft Fabric and Azure Synapse Analytics, addressing commonly asked questions about both solutions.
Azure Synapse is a PaaS for enterprise data warehousing, integration, and analytics. It was launched as a one-stop shop for all warehousing and analytics workloads. It included several tools bundled together in a platform called Synapse Studio.
Microsoft Fabric is built on an open, lake-centric design called OneLake. Fabric offers a comprehensive analytics solution that integrates various data services into a single, streamlined platform. This eliminates the need for organizations to combine disparate services from multiple providers, simplifying the process of data management. With features like OneLake, a unified data lake, and compatibility with Power BI, Microsoft Fabric provides a robust environment for data security, governance, and compliance, facilitating efficient data movement, integration, and real-time analytics.
Key features of Microsoft Fabric include OneLake, which centralizes data storage across various formats and sources, providing a unified data lake that facilitates access and analysis from a single location. The platform also features a Real-Time hub for the unification of data streams, allowing for real-time event routing and processing.
Additionally, Microsoft Fabric integrates AI capabilities, streamlining the transition from raw data to actionable insights. It offers a shared SaaS foundation, combining elements from Power BI, Azure Synapse Analytics, and Azure Data Factory into a cohesive user experience tailored for different roles within the data space.
Governance is enhanced by Purview, which is built into the platform, ensuring security and compliance across all data assets. With its unified approach, Microsoft Fabric simplifies analytics requirements and accelerates the data journey from ingestion to insights.
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Mapping of each Azure Synapse Feature in Microsoft Fabric
| Feature in Synapse | Feature in Fabric | Description of the difference |
| SQL Data Warehouse | Fabric Data Warehouse | It persisted in OneLake |
| SQL Serverless | Lakehouse SQL Endpoint | OPENROWSET syntax not supported yet in Fabric, but the structured data saved into Tables of the Lakehouse can be queries using SQL |
| Apache Spark Pools | Managed Spark Pools | Since it is a SAAS offering, Spark pools are managed by fabric itself. However, you can create your own environments of Spark version and load specific Python Libraries dynamically using Notebook |
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Apache Spark Notebooks
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Notebook | Fabric offers more features including Comments, co-editing with co-developer, data wrangler utility |
| Apache Spark Jobs | Spark Job Definition | |
| Data Explorer (KQL Scripts) | KQL Queryset | |
| Data Explorer Database | KQL Database | |
| Synapse Studio | Power BI Interface |
Fabric offers workspaces to manage various assets and access mapping using managed permissions.
Fabric offers persona specific experience for Data Engineering, Data Science, Warehousing, Real Time Analytics, Data factory, Data Activator |
| Git Integration | Git Integration | Fabric offers improvement in Git Integration via supporting native file formats for Notebooks instead proprietary JSON format adopted by Synapse. This makes it easier to track and manage changes |
| ML and ML Ops | Data Science | There is no need now to create another instance of Azure Machine Learning and then integrating with Synapse Environment. Experiments can be tracked, and Models can be deployed using MLFlow endpoints in Fabric. You can still perform EDA and other activities using Notebooks keeping continuity with existing Synapse platform |
| Mapping Data Flows | Not supported yet | You can use Dataflow Gen2 to achieve similar functionality |
| Synapse Link | This is yet to be supported in Fabric |
Significant Features and Enhancements in Microsoft Fabric
Significant Features & Enhancements in Microsoft Fabric
In the realm of SaaS analytics platforms, Microsoft Fabric stands out with its persona-based experiences, catering to various roles within an organization. For instance, a data engineer might engage with the Data Engineering experience to execute large-scale data transformations, while a data scientist could leverage the Data Science experience to develop AI models efficiently. This tailored approach ensures that each user interacts with the platform in a way that aligns with their specific role and responsibilities, enhancing productivity and streamlining workflows. Currently Fabric offers persona specific experience related to Power BI, Data Analytics, Data Science, Data Warehouse and Real Time Intelligence.
Direct Lake Mode
Direct Lake mode represents a significant advancement in data analysis within Power BI, offering a streamlined approach to handling large datasets. By directly loading parquet-formatted files from a data lake, it eliminates the need for querying a separate Lakehouse or warehouse, thereby simplifying the data management process. This method not only reduces the steps involved in preparing data for analysis but also enhances the speed at which insights can be derived, making it a valuable tool for businesses that handle extensive data volumes.
Copilot
The integration of Copilot and other generative AI features into Microsoft Fabric and Power BI represents a significant advancement in data handling and business intelligence. These tools are designed to streamline the process of data transformation, analysis, and visualization, making it easier for users to derive meaningful insights from complex datasets. With the power of AI, repetitive tasks can be automated, patterns can be identified more quickly, and reports can be generated with greater accuracy and detail. This not only enhances productivity but also allows businesses to make more informed decisions based on data-driven insights. As these features are still in preview, they offer a glimpse into the future of how AI will continue to revolutionize the field of data analytics and business reporting.
Currently Fabric offers Copilot for –
- Copilot for Data Science and Data Engineering
- Copilot for Data Factory
- Copilot for Power BI
- Copilot for Real-Time Intelligence
Governance and Compliances
Microsoft Fabric’s governance and compliance features are integral for organizations to handle sensitive information securely and efficiently. These capabilities, which are often included in the Microsoft Fabric license, enable businesses to adhere to data governance and compliance standards, thereby fostering customer trust. For certain advanced features, organizations may need to obtain additional licenses from Microsoft Purview, ensuring a comprehensive approach to data management and security. Using Governance and Compliances one can –
- Manage your data estate
- Secure, protect, and comply with standards
- Encourage data discovery, trust, and use
- Monitor, uncover, get insights, and act on it
Industry Solutions in Microsoft Fabric
Microsoft Fabric is designed to cater to the diverse needs of various industries, offering tailored data solutions that enhance data management and analytics capabilities. By addressing industry-specific challenges, it enables organizations to streamline operations, integrate disparate data sources seamlessly, and leverage advanced analytics for informed decision-making. This platform empowers businesses to harness the full potential of their data, driving innovation and efficiency across sectors.
- Currently Fabric offers data solutions for –
- Manufacturing data solutions in Microsoft Fabric (preview)
- Copilot template for factory operations on Azure AI (preview)
- Retail data solutions in Microsoft Fabric (preview)
- Sustainability data solutions in Microsoft Fabric (preview)
- Healthcare data solutions in Microsoft Fabric (preview)
- Healthcare data explorer in Microsoft Fabric (preview)
Limitations and Constraints
Since Fabric is still evolving with incremental features, there are certain constrains you as well need to consider –
Limited T-SQL Command Support
Fabric lacks T-SQL commands which were used in Synapse extensively. There are few alternatives as well but one has to take care of converting existing SQL statement using those unsupported functions with alternative approach.
Alternatively, one can get the data into Delta Format and query on top of it.
Few of the unsupported commands are Openrowset, Bulk Load, Grant, Deny, Revoke, Merge, Truncate, Alter Table and few more.
Data Type differences
Fabric does not support fewer common data types like datetime, images, text, money
For the list of unsupported datatypes and their alternatives, please refer to Microsoft Documentation here
Limitations to Data Warehouse Tables
For more information on known issues and limitations, please refer to Microsoft support sites
Microsoft is working on bringing these features over the period. Please stay tuned for updates.
Microsoft Fabric Adoption Roadmap
A roadmap for adopting Microsoft Fabric effectively involves a holistic approach that encompasses strategic planning, tactical actions, and cultural shifts within an organization. It’s not just about the technology; it’s about integrating it with the people and processes that drive your business. By focusing on these areas, you can foster a robust data culture that leverages Microsoft Fabric to its full potential, ensuring that data-driven decision-making becomes a natural aspect of your organization’s workflow. This integration is key to unlocking insights and achieving long-term success in today’s data-centric world.
Reference: Microsoft Fabric
Blog Author
Narendra Joshi
Project Delivery Head
Intellify Solutions