

Databricks and SAP Business Data Cloud are analytics solutions that compete in the big data and business intelligence sectors. Databricks has an edge in handling extensive data processing tasks due to its superior performance optimization and machine learning capabilities.
Features: Databricks specializes in large-scale analytics with optimized query performance. It includes built-in machine learning libraries significant for big data applications. The platform is efficient in processing large data volumes swiftly. SAP Business Data Cloud excels in creating visualizations and supports self-service platform functionalities. It facilitates intuitive planning and offers ease of visualization.
Room for Improvement: Databricks can improve its machine learning and visualization libraries to advance predictive analytics. Enhanced external platform integration and better automatic variable categorization are recommended. SAP Business Data Cloud could benefit from improved visualization features, better third-party system integration, and higher efficiency in planning functions, along with expanded connectivity options.
Ease of Deployment and Customer Service: Databricks offers flexible deployment primarily on public clouds and receives generally positive feedback for customer support, despite some reports of delayed responses. SAP Business Data Cloud also supports public cloud deployment and focuses on smooth integration with other SAP solutions. Users appreciate the comprehensive documentation and satisfactory technical support.
Pricing and ROI: Databricks is cost-effective with its pay-as-you-go model, facilitating resource scaling and strong ROI management in data-intensive operations. SAP Business Data Cloud offers competitive pricing in SAP ecosystems but can be expensive compared to alternatives like Power BI. Both pricing structures align with their targeted use cases, appealing to their respective operational strengths.
This reduction in both time and money resulted in real-time impact and significant cost savings.
For a lot of different tasks, including machine learning, it is a nice solution.
When it comes to big data processing, I prefer Databricks over other solutions.
We have saved a lot on the number of employees, and implementation time for the projects has reduced significantly since we started using the standard features of SAP Business Data Cloud.
Once the content is available, then it is a faster go-live with lesser cost in implementation, and that would give an ROI.
It will definitely reduce the need for more staff to handle this technology.
Whenever we reach out, they respond promptly.
As of now, we are raising issues and they are providing solutions without any problems.
I would give Databricks customer support a rating of ten.
The technical support is a very well-organized service, with a lot of tools for me as a consultant and for the end user on how to contact SAP support and get issues solved.
For example, when I provide a set of instructions, they often simply ask me to implement those steps without checking whether they are applicable.
In SAP's policy, for the first couple of years, the product team is also part of the support team.
The sky's the limit with Databricks.
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
Databricks is an easily scalable platform.
The scalability of SAP Business Data Cloud has been strong, as it has handled growth in data volume, user demand, and reporting requirements without significant performance issues.
SAP Analytics Cloud can be used by a small company, and it can be used by a large corporate.
Since SAP has consolidated everything on one platform, there is ample room to expand as much as needed.
They release patches that sometimes break our code.
Although it is too early to definitively state the platform's stability, we have not encountered any issues so far.
Databricks is definitely a very stable product and reliable.
You have a chance to test it on your test tenant in small increments, so it should not break your productive reports and productive environment.
It has been reliable for reporting, analytics, and data integration activities.
This really allowed virtual access to data, which means there was no heavy replication of data involved, greatly improving performance.
Adjusting features like worker nodes and node utilization during cluster creation could mitigate these failures.
We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly.
We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.
On the other hand, it is perfectly fitting to the SAP environment, with seamless integration to all SAP modules, not only ERP but also SuccessFactors and other tools from the SAP family.
If SAP can come up with innovative options to reduce licensing costs, many customers would incline toward SAP Business Data Cloud.
If I compare the cost with SAP competitors, I find that when creating an enterprise data lake, if I don't use SAP Business Data Cloud and make it directly in the hyperscalers, it is pretty much cheaper than doing the same in SAP Business Data Cloud.
It is not a cheap solution.
I believe that in terms of credits for Databricks, we're spending between £15,000 and £20,000 a month.
My experience with pricing, implementation costs, and licensing is that it is very efficient and very fast.
If I compare the cost with SAP competitors, I find that when creating an enterprise data lake, if I don't use SAP Business Data Cloud and make it directly in the hyperscalers, it is pretty much cheaper than doing the same in SAP Business Data Cloud.
From a planning license perspective, SAC on that side is very expensive if you need developer features.
SAP Business Data Cloud is at a disadvantage when compared to tools like Talend or Informatica, which are cheaper and more capable.
Databricks' capability to process data in parallel enhances data processing speed.
The platform allows us to leverage cloud advantages effectively, enhancing our AI and ML projects.
The Unity Catalog is for data governance, and the Delta Lake is to build the lakehouse.
For SuccessFactors and S/4HANA Cloud, there are pre-built reports available which are commonly used by customers.
SAP Business Data Cloud has positively impacted my organization by federating SAP data, which is now available for all to use.
The main standout feature is BDC Connect, as it is very useful for sharing data without replicating to third-party tools such as Enterprise Databricks, Snowflake or even in the near future, Google BigQuery as well as Microsoft Fabric.
| Product | Mindshare (%) |
|---|---|
| Databricks | 9.7% |
| SAP Business Data Cloud | 3.1% |
| Other | 87.2% |

| Company Size | Count |
|---|---|
| Small Business | 27 |
| Midsize Enterprise | 12 |
| Large Enterprise | 57 |
| Company Size | Count |
|---|---|
| Small Business | 44 |
| Midsize Enterprise | 21 |
| Large Enterprise | 64 |
Databricks offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.
Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.
What features make Databricks unique?
What benefits can users expect from Databricks?
In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.
SAP Business Data Cloud (SAP BDC) is a unified, intelligent data platform — part of the SAP Business AI Platform — that governs SAP and third-party data through a business data fabric. As an evolution of our industry-leading data, analytics and planning solutions, Business Data Cloud brings together Datasphere, Analytics Cloud, and Business Warehouse with a unified experience that delivers transformational insights across all lines of business. By harmonizing mission-critical data with the business processes and logic that give it meaning, SAP BDC delivers a trusted foundation for analytics and AI, empowering data teams and business leaders to make faster, more confident decisions.
What are the most important features of SAP Business Data Cloud?
What benefits or ROI should users look for in SAP Business Data Cloud?
SAP Business Data Cloud is a key component of SAP's vision for the autonomous enterprise. By unifying data connectivity, governance, semantic modeling, and analytics in a single cloud-native platform, SAP BDC eliminates fragmentation and complexity — serving as the connective tissue that ties your entire enterprise together and positioning organizations for long-term success in an AI-driven world.
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