Databricks offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service provides a platform for data pipelines, data lakes, and data platforms.
$0.07
Per DBU
Microsoft Fabric
Score 8.5 out of 10
N/A
Microsoft Fabric: A Comprehensive Data Management Solution Microsoft Fabric presents a unified, robust platform designed to optimize data management, enhance AI model development, and empower users across an organization. It focuses on integrating data seamlessly, ensuring governance and security, and providing AI capabilities. Microsoft Fabric is presented as an all-encompassing data management solution, providing organizations with tools for efficient data integration,…
N/A
Pricing
Databricks Data Intelligence Platform
Microsoft Fabric
Editions & Modules
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
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Offerings
Pricing Offerings
Databricks Data Intelligence Platform
Microsoft Fabric
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Use Microsoft Fabric by purchasing Fabric Capacity, a billing unit that enables each Fabric experience. Pay for every data tool in one transparent, simplified pricing model and save time for other business needs.
Fabric Capacity is priced uniquely across regions.
Medium to Large data throughput shops will benefit the most from Databricks Spark processing. Smaller use cases may find the barrier to entry a bit too high for casual use cases. Some of the overhead to kicking off a Spark compute job can actually lead to your workloads taking longer, but past a certain point the performance returns cannot be beat.
I would highly recommend Microsoft Fabric, especially for medium to large enterprises aiming to build a robust, scalable, and secure data analytics platform. It effectively unifies various data workloads, streamlining data integration, engineering, and particularly enhancing our ability to create and share reliable Power BI dashboards. The deep integration with Azure AD for features like Row-Level Security is a significant advantage for data governance.
Connect my local code in Visual code to my Databricks Lakehouse Platform cluster so I can run the code on the cluster. The old databricks-connect approach has many bugs and is hard to set up. The new Databricks Lakehouse Platform extension on Visual Code, doesn't allow the developers to debug their code line by line (only we can run the code).
Maybe have a specific Databricks Lakehouse Platform IDE that can be used by Databricks Lakehouse Platform users to develop locally.
Visualization in MLFLOW experiment can be enhanced
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.
in terms of graph generation and interaction it could improve their UI and UX
I've rated Microsoft Fabric's overall usability as a 4, primarily due to its extensive and multifaceted feature set, which can make it challenging to navigate and determine the optimal functionality for a given task.While the breadth of capabilities is a core strength for large enterprises, it often leads to a sense of being "lost" or overwhelmed for teams like ours that do not have highly formalized roles or dedicated specialists for each Fabric "experience" (e.g., Data Engineering, Data Warehousing, Data Science).
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when it comes to Spark Job Execution. Other platforms need to be self-managed, which is another huge hassle.
Microsoft Fabric integrates data ingestion, engineering, warehousing, and Power BI visualization into one cohesive environment. This "one-stop shop" approach dramatically reduces complexity, minimizes operational overhead, and eliminates the need to integrate disparate tools and manage data across multiple systems. It provides superior scalability for large datasets, supports open data formats, and offers a much broader suite of data engineering and data science capabilities.In essence, Fabric's integrated ecosystem and streamlined operational management were key differentiators, providing a more cohesive, scalable, and efficient solution for our evolving data strategy than combining specialized tools.
