What is Microsoft Fabric, And How Does It Differ from Synapse Analytics? - Netwoven

What is Microsoft Fabric, And How Does It Differ from Synapse Analytics?

By Gjnana Prakash Duvvuri  |  Published on October 7, 2023

What is Microsoft Fabric, And How Does It Differ from Synapse Analytics?

Microsoft Fabric, a new data and AI platform solution, was recently introduced by Microsoft. It is a unified SaaS platform that has been expanded with current Microsoft analytical tools like Azure Synapse Analytics, Azure Data Factory, Azure Data Explorer, and Power BI. It will facilitate seamless data exchange, easy data discovery, and reduced integration time and effort.

Fabric’s data and workloads are stored in the centralized repository called OneLake. OneLake is a single, unified, logical data lake for the whole organization. OneLake is multi-cloud data lake allows enterprises to virtualize data lake storage in ADLS Gen2, AWS S3, and Google Storage (coming soon). You can use your existing data lakes within Fabric.

Within Fabric, all data is preserved in delta lake format. Even warehouse data is preserved in delta format. Relational storage is no longer available. Customers are therefore relieved of the burden of maintaining separate data sets for data lakes, data warehousing, business intelligence, and real-time analytics. Instead, all the workloads can be directly powered by a single copy of the data in OneLake.

Microsoft will soon incorporate Copilot into Fabric, allowing users to design dataflows and data pipelines and write code using conversational language. You can conclude that Fabric offers nearly all Synapse functionalities by looking at the architecture mapping in the image.  

Compare Differences. Synapse Analytics vs Microsoft Fabrics

What is Microsoft Fabric, And How Does It Differ from Synapse Analytics?
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How does it differ from Synapse Analytics?

  • Fabric is a SaaS (less control and fully managed service), whereas Synapse is a PaaS (more control and more responsibility).
What is Microsoft Fabric, And How Does It Differ from Synapse Analytics?
  • Unlike Synapse, Fabric does not have a dedicated SQL pool or relational storage. In Fabric, warehouse data is persisted in delta lake format.
  • Fabric warehouse is powered by the Polaris engine, which also drives the Serverless SQL pool in Synapse. This MPP (massively parallel processing) engine scales AUTOMATICALLY to accommodate different data workloads.
  • Dataflows Gen2 (Power Query) can be used in place of Mapping Data Flows since Fabric does not support them. Synapse Mapping Data Flows is the “no code / low code” graphical user interface that can be used to transform data in Synapse.
  • Fabric does not allow OPENROWSET(). You may still query the data from the lake(house) in Fabric using T-SQL, but you must modify all queries that utilise OPENROWSET syntax.
  • Synapse Link feature is not available in Fabric. Synapse Link allows to query the data from Cosmos DB and/or Microsoft Dataverse.
  • The Data Activator module, which is new in Fabric, is designed for real-time data detection and monitoring. It will be able to send notifications and perform actions when it detects specific patterns in data.
  • The Spark engine in Fabric spins up significantly faster than the Synapse engine.

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Fabric enables next-generation data and analytics capabilities such as Lakehouse, Data Mesh, and Data Virtualization. However, keep in mind that everything announced is still in preview. Organizations that utilize Azure Synapse Analytics should consider Microsoft Fabric and how it fits with their technological roadmap. Certain Synapse features (most notably, Mapping Dataflows and OPENROWSET() syntax in SQL queries over files in a data lake) are not supported in Fabric. There is right now no “lift-and-shift” approach to migrating from Synapse to Fabric.

By Gjnana Prakash Duvvuri

Gjnana has an impressive 24 years of experience in IT, with a particular focus on cloud architecture consulting and IT technical leadership. He has worked with big-name clients such as Microsoft, Union bank(MUFG), Delta Airlines, BCBS, Macys, Global Payments, and UPS, supporting their large transformative initiatives. Over the last 7 years, Gjnana has been specializing in cloud platforms such as Azure, AWS, Oracle, and Google. His main area of focus is Digitalization Data & AI, Open Analytics, SAP Integration, Modern data warehousing with BI & AI on end-to-end implementations with data services, app modernization, and on-prem to cloud migrations. With his deep understanding of business domain operations in industries such as Financial Card Merchant Services, Banking, Retail, Supply Chain Management, Manufacturing, Pharmaceuticals, Pharma product management, Healthcare, Biotechnology, Oil & Gas, Travel and Transportation, Gjnana shares technical and domain knowledge through webinars and blogs.

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