I like how SAP Datasphere centralizes, models, and analyzes data from different systems, creating a unified data layer and enabling faster, more reliable reporting. It preserves SAP's business context while letting me combine data from multiple sources, making modeling faster and keeping everything consistent. I appreciate the handling of semantic modeling and data federation, allowing me to reuse SAP business logic and connect external sources without heavy ETL. The self-service modeling reduces back-and-forth with IT, and the interface is simple to navigate, making initial setup fairly easy. Review collected by and hosted on G2.com.

Performing at scale, the complexity of the modeling layers, and the learning curve. SAP Datasphere can feel slow with large datasets, and managing Spaces, permissions, and semantic models sometimes becomes more complicated than necessary. Pricing based on consumption can also be unpredictable if you don't monitor usage closely. Review collected by and hosted on G2.com.

SAP Datasphere has come a long way on the interface front. It's genuinely more usable than most SAP products, with a drag-and-drop modeler that business users can actually figure out, though it still takes time to get comfortable with the full platform.

Where it really shines is in integrations. It connects deeply into the SAP world but has opened up significantly, with solid links to Snowflake, Databricks, and Microsoft Fabri, so you're not trapped in one ecosystem. Performance is strong under the hood thanks to HANA Cloud, and if you're migrating from older SAP systems, you'll feel the difference straight away.

Pricing isn't entry-level, but the SaaS model means you're not writing a huge check upfront; you grow into it. The ROI makes most sense if SAP is already your core stack. On support and onboarding, be honest with yourself: this isn't a tool you roll out casually. It needs a real implementation plan and ideally a good partner alongside you.

The most exciting part right now is AI. The whole platform is clearly being architected with AI at the center, feeding SAP's Joule assistant, enabling governed data access for AI agents, and building toward a future where your data actually powers intelligent decisions rather than just reports. That direction alone makes it worth watching closely. Review collected by and hosted on G2.com.

The complexity is real, and it doesn't apologize for it. Getting up and running takes significant time, money, and expertise. This is not a tool you hand to a team and expect results from quickly. Without a proper implementation partner, you'll struggle.

The pricing lacks transparency. It's hard to predict what you'll actually spend as your usage grows, and costs can creep up in ways that are difficult to plan for upfront.

It still feels very SAP-centric at its core. While the third-party integrations have improved, the platform clearly works best when you're living inside the SAP ecosystem. If you're not, you'll constantly feel like you're working against the grain rather than with it.

The pace of change, while impressive, is also a double-edged sword. Features arrive frequently, but documentation doesn't always keep up, leaving teams to figure things out through trial and error or expensive consulting hours.

And despite the progress on UI, it still carries that distinctly SAP-heavy feel, with navigating the platform feeling bureaucratic, with too many layers between you and what you're actually trying to do. For business users especially, the learning curve remains steep enough to push people back toward their old spreadsheets. Review collected by and hosted on G2.com.

I appreciate SAP Datasphere for making my daily tasks easier, which helps me grow my clients. The platform has significantly reduced the time required to complete tasks from hours to just a fraction of minutes. I admire the user experience and the ease of use of the platform, which is seemingly based on user-centric design. Even as a complete beginner, I found the initial setup process to be the easiest and incredibly simple. Review collected by and hosted on G2.com.

Few points like the costing of it is a bit higher. Let's say for now only 5 of my team members are able to work on it due to the costing and if the cost is cheaper we could onboard more members. Review collected by and hosted on G2.com.

I like SAP Datasphere because it creates a single, reliable source of truth by integrating and modeling data efficiently. This makes reporting faster and more consistent. Its efficient data integration reduces manual work and speeds up data availability, allowing us to make faster, more accurate decisions and deliver reliable insights through tools like Power BI. Review collected by and hosted on G2.com.

Learning curve – Takes time to understand modeling and architecture Performance – Can slow down with large or complex datasets Cost – Pricing can be high for scaling usage Flexibility – Less intuitive for non-SAP or custom integrations Review collected by and hosted on G2.com.

I like that SAP Datasphere simplifies a messy data landscape by bringing data together from different sources in a structured and meaningful way. It not only centralizes data but also helps maintain the business meaning behind it, making reporting more accurate and useful. It serves as a tool that supports both technical teams and business users by enabling them to work with the same trusted data efficiently. I appreciate that it unifies data understanding and governance, providing a single source of truth. Review collected by and hosted on G2.com.

I think the SAP Data Studio is powerful, but there is a learning curve behind it, and it can be a bit steep for some people. Some parts can be more intuitive and friendly in my opinion. The setup was okay, but it takes some time, and it's not what I would call a simple plug and play. Review collected by and hosted on G2.com.

What I like most about Sap DataSphere is its strong integration capability and with sap ecosystem and other external data source its allow seamless data intergration,modeling and virtualization, Review collected by and hosted on G2.com.

its learning curve , especially for user who are not already familiar with the SAP ecosystem. setting up and configuring data models can sometime feel complex. Review collected by and hosted on G2.com.

I like that SAP Datasphere makes data from different systems easier to access and combine. The data modeling is quite flexible, and it helps create structured views for reporting. It also integrates well with other SAP tools, which makes analytics and data sharing smoother. Data modeling helps us structure the data in a way that is easier for reporting and analysis. Flexible access simplifies working with data from different sources without heavy manual preparation, and integration with other SAP tools helps share data more easily across systems and teams. Review collected by and hosted on G2.com.

Sometimes performance can be a bit slow when working with large datasets. Also, the interface and data modeling can feel a bit complex at the beginning. Better documentation and simpler configuration for some integrations would also help. Integrations with some non-SAP systems can be a bit challenging, especially when setting up connections or aligning the data structures. Sometimes it requires additional configuration or middleware. It would be helpful if the setup process were more straightforward and better documented. The initial setup was a bit tricky at first, especially configuring connections and modeling data. Review collected by and hosted on G2.com.

I appreciate SAP Datasphere's robust security, ensuring my data is well-protected. The multiplier storage efficiency is a standout feature, making it very easy for me to manage data, ensuring everything is in the appropriate storage. I find it beneficial to keep hot and active data in mentor while moving warm or cold data to disk, which optimizes performance and costs for me. Review collected by and hosted on G2.com.

It's very expensive. The system is very complex and requires a lot of training. The initial setup was pretty complex, and I needed assistance from IT. Review collected by and hosted on G2.com.

I really appreciate that SAP Datasphere offers a single, trusted view of data across different systems without needing to constantly move or duplicate large datasets. I love how you can connect to data where it already lives and still analyze it as one unified model. I also value its flexibility, better cloud integration, and easier real-time access to data across multiple systems. Review collected by and hosted on G2.com.

It can be complex to set up, has a steep learning curve, and sometimes performance and permissions management can be challenging at scale. Simpler onboarding with guided setup for first-time data models and connections, better performance optimization tools for large virtualized datasets, and more transparent monitoring would improve SAP Datasphere. Review collected by and hosted on G2.com.

What I like most about SAP Datasphere as a data engineer in the NHS is its strong governance and seamless integration with core SAP systems like SAP S/4HANA. It allows me to build trusted, well-structured data models while maintaining strict security and compliance standards. That reliability is crucial in a healthcare environment where accurate reporting directly supports operational and financial decision-making. Review collected by and hosted on G2.com.

One thing I dislike about SAP Datasphere is that it can feel rigid and less flexible compared to more modern data platforms. Development and modelling can be slower than expected, especially for complex transformations. It can also be frustrating when performance tuning and troubleshooting aren’t as transparent or straightforward as you’d like. Review collected by and hosted on G2.com.