What I like best about Microsoft Fabric is that everything is available in one platform. We can use Data Factory, Data Engineering, Data Warehouse, Power BI, and other services without depending on too many different tools.

I also like OneLake and the Lakehouse concept, because it makes the data management much easier. The integration with Power BI and Direct Lake is also very useful, as we can work with the data and build reports more easily. Review collected by and hosted on G2.com.

One thing I dislike about Microsoft Fabric is that sometimes the platform is still changing and some features are not fully stable. We may face issues with performance, capacity, or some features not working as expected.

Also, troubleshooting some Fabric issues is not very straightforward, especially when we are working with different workloads like Lakehouse, Warehouse, Pipelines and Power BI. Sometimes it takes more time to identify the actual root cause. Review collected by and hosted on G2.com.

The best thing about Microsoft Fabric is its unified experience. It brings together data integration, engineering, warehousing, and reporting in a single platform, which makes it easier to build and manage end-to-end analytics solutions. As a result, it reduces complexity and helps improve productivity. Review collected by and hosted on G2.com.

The biggest drawback for me is the learning curve. Because Microsoft Fabric brings multiple data and analytics services together in a single platform, it takes time to fully understand everything it can do, and some of the newer features still feel like they’re maturing. Review collected by and hosted on G2.com.

Microsoft Fabric is easy to use for designing and implementing data analytics workflows. It offers built-in data connectors such as OneDrive, along with a drag-and-drop workspace that simplifies development and collaboration.

It makes it easy to manage and publish analytics solutions using multiple data sources and connectors. It also integrates well with Azure-hosted data and Power BI dashboards. It has access control and permission management features that help secure sensitive data and support team collaboration across projects. Review collected by and hosted on G2.com.

Users who are not already familiar with Microsoft solutions may find the platform overwhelming at first. Understanding Fabric’s capabilities, integrations, and data connectors often requires guidance from experienced team members. Review collected by and hosted on G2.com.

What really stands out about Microsoft Fabric is how it brings everything into one place. Combining Data Factory and OneLake cut down a lot of the back end effort we used to deal with when managing separate pipelines and storage, and it made data more consistent across teams.

From a usability standpoint, the interface is fairly intuitive once you spend some time with it. It is not overly complex but there is still a bit of a learning curve if you're coming from traditional Azure tools, mainly because everything is now bundled into a single experience rather than separate services.

The Power BI integration was another big win. We did not have to rebuild existing reports we were able to extend what we already had, which made adoption much easier for business users. Direct Lake has also helped improve performance, especially for larger datasets, without adding extra layers of complexity.

We have also seen solid value from Synapse Real Time Intelligence. It has given us a practical way to move toward real time visibility for certain use cases which was difficult to achieve with our earlier batch driven setup. From an AI and analytics perspective, having these capabilities closer to the data layer makes it easier to experiment with more advanced use cases over time.

In terms of pricing, the consumption-based model gives flexibility, but it takes some time to understand how workloads translate into actual costs. We had to actively monitor usage in the beginning to avoid unexpected spikes and improve ROI.

Support and onboarding were decent overall but most of the learning came from hands on experience and internal experimentation rather than formal guidance.

That said it is not completely straightforward. Teams coming from traditional Azure services should expect a learning curve. The capacity based model can be confusing at first and governance needs to be set up early to keep costs under control as adoption grows. Review collected by and hosted on G2.com.

What we have found challenging with Microsoft Fabric is that moving to a unified platform comes with some trade offs. The UI is clean but it can feel overwhelming at first since multiple services are bundled into the same workspace. For teams used to separate Azure tools just figuring out where everything sits takes some adjustment.

The pricing model has been another headache. Since it is consumption-based and tied to Capacity Units (CU) costs are not always easy to predict especially when workloads scale or multiple teams are using the platform at the same time. We have had to closely monitor usage to avoid unexpected spikes and better understand the actual return on spend.

From a day to day operations perspective some of the monitoring and debugging capabilities still feel early compared to standalone Azure services. Getting clear visibility into pipeline failures or performance bottlenecks is not always as straightforward as it should be.

Onboarding could also be smoother. While documentation exists much of the learning has come through trial and error rather than structured guidance particularly for more advanced scenarios.

Finally while Fabric is pushing into AI and real time capabilities some of these features still feel like they are evolving. They are useful but not always as mature or flexible as expected for more complex production use cases. Review collected by and hosted on G2.com.

Microsoft Fabric is essentially the "SaaS-ification" of data. The best parts are:

​OneLake: A single "OneDrive for data" that eliminates silos.

​No-Copy Architecture: Using "Shortcuts" to access data (even from AWS or GCP) without moving or duplicating it.

​Direct Lake Mode: Allowing Power BI to analyze massive datasets instantly without the usual "import" lag.

​Unified Experience: One portal where data engineering, science, and analytics finally live together. Review collected by and hosted on G2.com.

It prioritizes ease of use, power users often find they have less control over fine-tuning performance compared to dedicated, standalone tools.

Microsoft Fabric's biggest drawbacks are its relative immaturity and the "walled garden" risk, which can lead to vendor lock-in. The SaaS pricing model can also be unpredictable, making it difficult to manage costs during high-usage periods. Review collected by and hosted on G2.com.

Microsoft Fabric provides customers with a unified workspace that brings together Data Engineering, Data Science, and Data Analytics. Microsoft Fabric helps to combine data from various data sources, such as Microsoft Azure Portal, Office 365, and Power-BI, into a single, unified Platform. At Blue Yonder, we have integrated it easily with the critical Microsoft solutions like O365, Microsoft Teams, and Azure Ai Solution. Review collected by and hosted on G2.com.

The resource utilization should be bit reduced. Review collected by and hosted on G2.com.

One thing I like about Microsoft Fabric is how it brings multiple data capabilities into a single platform. Instead of using separate tools for data storage, transformation, and analytics, Fabric keeps most of the workflow in one place, which makes things easier to manage.

In my case, I mainly work with the Fabric warehouse where we store tables and create views that are later used for reporting. The platform is fairly easy to use once you get familiar with the interface, and implementation was quite straightforward since our team already uses Microsoft tools.

Another strong point is integration. Connecting Fabric warehouse data to Microsoft Power BI for dashboards works smoothly, which helps simplify the reporting workflow. I also like that Fabric includes multiple features like lakehouse, warehouse, and data pipelines in one environment, so teams can manage different data tasks without switching platforms Review collected by and hosted on G2.com.

Since Fabric is still relatively new compared to some older data platforms, sometimes documentation for certain scenarios is limited. It can take a bit of experimentation to figure out the best way to organize the data between lakehouse and warehou Review collected by and hosted on G2.com.

Microsoft Fabric is a great platform for organizing data that’s scattered across different platforms and turning it into something valuable, especially since data is now one of the main supplements for business. It can be easily interegated with many platforms from my local DMS system to normal HRIS to our other web applications. Friendly UI, best performance with zero code based powered by Copilot AI with minimum pricing and prompt support from local microsoft partner makes fabric more workable and useful for all type of organizations. Review collected by and hosted on G2.com.

I am still learning how to use and best optimize my business needs. So I haven't faced any issues or things that I dislike about Fabric. Review collected by and hosted on G2.com.

What I like best about Microsoft Fabric is its unified platform that brings together data engineering, ETL, analytics, and visualization seamlessly. It integrates services like Data Factory, OneLake, and Power BI, which reduces data movement and overall complexity. Fabric supports easy CI/CD through Git integration and enables near real-time data access with database mirroring. With its single capacity-based pricing model, simple implementation, and built-in support for the medallion architecture, it is both cost-effective and easy to use. Review collected by and hosted on G2.com.

What I dislike about Microsoft Fabric is that it is still evolving, so some features feel less mature compared to standalone Azure services. There is also a learning curve, especially for users new to the unified Fabric experience. At times, documentation and troubleshooting guidance can be limited, which makes resolving issues a bit challenging. Review collected by and hosted on G2.com.

One Platform for Everything, No more “tool chaos”. Fabric’s OneLake is one of its most loved features, a single, AI-ready data lake with unified governance and shared datasets. Fabric combines Power BI, Azure Data Factory, and Synapse Analytics under one roof. Review collected by and hosted on G2.com.

Fabric is complex to learn, especially because it unifies many tools (Power BI, Synapse, Data Factory, etc.) into one platform. Review collected by and hosted on G2.com.