SAP Datasphere Reviews & Product Details

Spaces = clean isolation. I can spin a sandbox space per branch, wire connections, and run pipeline tests without stepping on prod models. It’s the right level of multi-tenant for QA.

Semantic layer with teeth. Business entities/measures live in one place (dimensions, associations, units/currencies). We write “contract tests” against the model, not brittle SQL, if someone drops a KPI or changes a type, CI fails loudly.

Virtualize first, replicate when needed. Being able to federate queries to S/4HANA/BW or stage extracts into HANA Cloud keeps performance decent while avoiding data sprawl. Our tests cover both paths using the same artifacts.

Decent lineage & impact analysis. When a column rename lands upstream, lineage shows which views/calculations break. I can link an impact report to a failing test and the owner knows exactly where to patch.

Transportable configs. Moving artifacts from dev -> test -> prod is predictable; we version transports next to our test code, so rollbacks are boring.

BW Bridge for the real world. Legacy BW content doesn’t block us; we can validate migrated models side-by-side with new ones until parity tests pass.

Tight with SAC. For UAT, we point a SAC story at the test space and stakeholders validate numbers without bespoke extracts. Review collected by and hosted on G2.com.

UI latency at scale. Big models make the modeling UI feel heavy; complex Data Flows are sluggish to edit.

Error messages are terse. Federation/privilege errors often read like riddles, you end up checking remote system logs to learn what actually failed.

Transform limits. Graphical transforms cover 80%; the last 20% still needs SQLScript or external prep.

Transport gotchas. Dependency ordering can bite, miss one shared artifact and your pipeline deploy looks “green” but doesn’t run. Review collected by and hosted on G2.com.

Easy to use no need for prior specific education! Thanks for the SAP provideers and for my company to choose SAP.

In addition, SAP Datasphere is a unified, cloud-based data service built on the SAP Business Technology Platform (BTP) that provides a comprehensive business data fabric for data integration, cataloging, semantic modeling, data warehousing, and virtualization across SAP and non-SAP data sources. Review collected by and hosted on G2.com.

Dislikes about SAP Datasphere include high costs and lack of scalability for small businesses, performance issues with large datasets, complex integration with non-SAP tools, a steep learning curve, intricate data modeling and setup processes, and frequent, sometimes disruptive UI changes. Review collected by and hosted on G2.com.

What I appreciate most is the ease of integration. Since I work with automation frameworks such as Python and Jenkins, I need tools that can interact seamlessly with my scripts, and Datasphere does this very effectively through its CLI. I don't have to manually navigate the UI to deploy changes or set up a test space. I simply run a command and it's taken care of. This also contributes to the ease of implementation. Moving a new data model from development to a QA environment is straightforward because we can automate the entire upload process. It saves us a significant amount of time. I use Datasphere constantly, pretty much every time a developer commits code, and it manages the frequent updates without any issues. Honestly, what I value most is being able to skip the manual steps and manage the infrastructure as code. Review collected by and hosted on G2.com.

Honestly, the documentation for specific CLI commands can sometimes be a bit sparse. For example, when I encounter an unusual edge case while scripting a deployment, it often takes considerable effort to track down the exact flag I need. Additionally, when automation fails, the error messages returned by the CLI are often vague. Sometimes, it simply reports 'failed' without specifying which part of the JSON model was incorrect, which means I end up spending extra time debugging or combing through logs. Once everything is set up, it works very well, but troubleshooting during the setup phase can be frustrating. Review collected by and hosted on G2.com.

Available as a service, this solution does not require dependence on the traditional BW system from SAP. It allows data to be transferred to multiple targets, and I found the integration with Snowflake to be straightforward and effective. Review collected by and hosted on G2.com.

The CDS views and customization options on the S/4 side still feel somewhat immature. Additionally, the note analyzer, which serves as a backbone for addressing bugs in S/4, is updated too frequently and requires a significant amount of ongoing maintenance. Review collected by and hosted on G2.com.

What I like best about SAP Datasphere is how seamlessly it brings together data from SAP and non-SAP systems into a single, well-governed semantic layer. The unified modeling experience, strong business context, and built-in governance make it much easier to maintain trustworthy data across complex landscapes. Its ability to virtualize data without heavy replication also saves time, reduces overhead, and keeps data fresh. Overall, Datasphere lets teams get to insights faster with far less integration effort. Review collected by and hosted on G2.com.

While SAP Datasphere is powerful, a few areas still need improvement. The performance can slow down when working with large virtualized datasets, and some advanced features require additional configuration or licensing, which increases complexity. The UI, though improved, can feel less intuitive for complex modeling tasks. Integration with certain non-SAP sources also requires extra setup, and debugging data flows isn’t always straightforward. Review collected by and hosted on G2.com.

I appreciate the seamless integration SAP Datasphere offers with both SAP and non-SAP sources, which keeps the data context intact. The strong data modeling and semantic capabilities make it easy to build reliable analytical layers. Additionally, I value the real-time data access, which enhances collaboration between business and IT teams, allowing everyone to use the same trusted data without duplication or complex transfers. The data modeling layer and data federation features are particularly valuable because they enable us to combine data from multiple systems without moving it, saving time and maintaining data consistency across the organization. The transition from SAP Data Warehouse Cloud to SAP Datasphere has been beneficial, providing us with more advanced data integration, better governance features, and improved flexibility for managing complex data landscapes. The initial setup was generally smooth, especially for SAP integrations, and the guided setup, along with the available documentation, made the process manageable. Review collected by and hosted on G2.com.

Some configurations can be a bit complex, especially when setting up permissions and roles. Performance could also improve when handling very large or highly complex data models. Better documentation and examples would help new users get started faster. Review collected by and hosted on G2.com.

This tool is very user-friendly and truly amazing, making it accessible to anyone without the need for training or documentation. You can set up your workflows easily and without any complications. If you ever encounter any difficulties, the support team is responsive and helpful. I regularly use datasphere for both my company and personal needs. Review collected by and hosted on G2.com.

So far, there isn't anything I dislike. While there is room for improvement in terms of functionality and available options, it works well for beginners. However, if you try to implement more advanced logic, you might encounter strange errors, issues with caching, and longer rendering times. Review collected by and hosted on G2.com.

I think SAP Datasphere is very user-friendly compared to other enterprise data management tools. The interface is intuitive, and it allows seamless integration with different data sources. I particularly like how it combines data modeling, governance, and analytics capabilities within a single environment, making it easier to connect business users and technical teams. Its compatibility with SAP and non-SAP systems also adds great flexibility for organizations managing complex data landscapes. Review collected by and hosted on G2.com.

While SAP Datasphere is powerful, its initial setup and configuration can be quite complex for new users. The documentation could be more detailed, especially when it comes to advanced integrations. Additionally, performance can sometimes slow down when handling very large datasets, and pricing may be on the higher side for smaller organizations. A more streamlined onboarding experience and better customer support responsiveness would make it even more efficient. Review collected by and hosted on G2.com.

What I like best about SAP Datasphere is its seamless integration with core SAP applications combined with the ability to preserve business semantics and context in data models. This makes it much easier to create trustworthy, business-ready data products that can be used consistently across analytics and planning solutions. In addition, I value the flexibility to connect SAP and non-SAP data sources in one governed environment, enabling a holistic view of enterprise data without losing performance or control. Review collected by and hosted on G2.com.

What I dislike about SAP Datasphere is that it can feel complex and resource-intensive to set up, especially when integrating large volumes of non-SAP data. Some features are still maturing, and performance can vary depending on the data source. In addition, the cost model may become challenging as usage scales, which requires careful planning. Review collected by and hosted on G2.com.

Best about SAP Datasphere.

I like that it connect very smooth with SAP systems. I worked only once with this product, one of our clients using S/4HANA, and Datasphere made it easier to bring sales and finance data together without building so many ETL flows. Also the business layer is helpful, because we can show data in more “business words” not only technical.

Most helpful about SAP Datasphere

For me the most helpful thing is we can centralize SAP + other data in one place. In BigMoney Analytics, which is our small company that works with automation analytics of small and medium businesses, we don’t need to spend too much time building custom pipelines, because Datasphere already handle part of it. That save us time and help us deliver Power BI dashboards quicker to clients.

Upsides of using SAP Datasphere

Easy to connect to SAP sources, less headache.

Business friendly modeling, not only for IT guys.

Combine ERP operations with finance reporting.

Faster time to deliver analytics, which our client like a lot. Review collected by and hosted on G2.com.

I only worked with SAP Datasphere one time, in a project for one of our clients. From this limited experience, the main thing I didn’t like was the performance when data stay virtualized. For bigger tables the queries was slow, and finally we needed to replicate part of the data which made the setup more heavy. Also the licensing and cost is not so clear, it looks like it can get expensive fast when you scale. Since it was just one project, maybe I didn’t explore everything, but I also felt non-SAP integrations are not so strong, we had to do extra work to connect other systems. It looks powerful, but at this stage I think the product is still maturing and missing some advanced functions compared to older SAP tools Review collected by and hosted on G2.com.