Native SAP HANA data warehousing
As a short introduction, we all know that the world of SAP modeling systems is multifaceted and complex. Native SAP HANA data warehousing refers to the process of designing, developing, and maintaining data warehouses exclusively within the SAP HANA platform.
Data warehousing is essential for businesses looking to make data-driven decisions. It involves collecting, storing, and analyzing data from various sources to gain insights and support decision-making.
Obviously, such comprehensive solutions, which have grown over the years, cannot easily be distinguished from each other in a single short text, especially since topics such as know-how, licenses, and strategy must always be included individually in the analysis.
To be able to at least roughly separate the solutions conceptually, we deliberately refrained from examining all technical options in a single blog. One of these options includes the enhancement of native SAP HANA modeling with explicit data warehouse functions (known as SAP HANA for SQL data warehousing).
SAP HANA for SQL data warehousing is a solution that enables experienced SAP Business Warehouse customers and new customers to design, build, and operate their own data warehouse using native SAP HANA tools. Both SQL-based development and graphical editors can be used to meet the requirements for harmonization, strategic reporting, and data integration.
The upcoming blog series on this topic is intended to give you a classification of this solution and briefly present its essential core components:
- SAP HANA for SQL data warehousing – Positioning
- SAP HANA for SQL data warehousing – Core Components
- SAP HANA for SQL data warehousing – data warehousing foundation
1. SAP HANA for SQL Data Warehousing – Positioning
SAP HANA for SQL data warehousing is a native SQL data warehousing approach that is implemented with the SAP HANA platform on-premise. This solution can be seen as an extension of the frequently used pure virtual approach to modeling in SAP HANA (mainly with the calculation views). The actual enhancement comprises tools and objects that are aimed in particular at persisting the data models. With SAP HANA as the foundation of SAP HANA for SQL data warehousing, not only does the system speed benefit from all known HANA-specific performance drivers (among others: in-memory), but also its functional scope by the Advanced Analytics package (among others: predictive, geospatial, and graph data processing).
The fact that SAP HANA for SQL data warehousing is an SQL-based development (graphical and/or script) results in a largely open system landscape with regard to communication and virtualization. This means that, in addition to SAP-specific tools such as SAP Analytics Cloud or SAP Analysis for Microsoft Office, third-party tools can also be connected.
As mentioned above, it is up to you ,as a customer, to decide in which cases they want to be used for the graphical development (calculation view or nDSO, for example) or rather for script-based development (among other things: Functions or Procedures). In both approaches, SAP HANA for SQL data warehousing provides graphical and script-based editors, which are supported with the Git-enabled SAP Web IDE for SAP HANA.
By working with SAP HANA extended application services, advanced model, this solution also incorporates the microservice architecture, with which multiple runtimes are possible in a system environment and developments made can also be operated in the cloud.
In addition to these topics, a holistic data warehouse solution also includes classic functions such as data integration, delta capability, persistence, and monitoring. These aspects will be covered in our next blog “ SAP HANA for SQL Data Warehousing – Core Components”.
In conclusion, by utilizing native SAP HANA data warehousing, organizations can harness the full potential of the SAP HANA platform to store, manage, and analyze their data efficiently. This results in improved business intelligence, better decision-making, and increased competitiveness in the market.
Are you interested in getting to know the above benefits and facets of this solution in more detail? Then please take our course on this topic via our free learning journey in new learning site : learning.sap.com.
I have the following questions:
1) Is SAP HANA for SQL Data Warehousing only supported for on-premise or does it apply to SAP HANA Cloud as well?
2) What would be the reasons for choosing SAP HANA for SQL Data Warehousing over SAP Datasphere?
Thanks for your questions. Let me try to answer them.
1. SAP HANA for SQL Data Warehousing is supported both for on-premise and SAP HANA Cloud deployments. SAP HANA Cloud is an extension of the on-premise SAP HANA platform, offering similar capabilities and features but in a cloud-based environment.
In SAP HANA Cloud, you can leverage the power of SAP HANA for data warehousing, enabling you to build, deploy, and manage data warehousing solutions in a cloud-based environment. This allows you to take advantage of scalability, flexibility, and cost-efficiency that cloud infrastructure provides.
2. SAP HANA and SAP Datasphere (previously known as SAP Data Warehouse Cloud) are both data management and analytics solutions, but they have different architectures and use cases. Choosing between them depends on your organization's requirements, budget, and existing infrastructure.
Here are some reasons why you might choose SAP HANA for SQL Data Warehousing over SAP Datasphere:
- In-memory capabilities: SAP HANA is an in-memory database designed to process high volumes of data in real-time.
- On-premise deployment: SAP HANA can be deployed on-premise, which may be preferred by organizations with strict data security requirements or those that want to maintain control over their infrastructure. SAP Datasphere, on the other hand, is a cloud-based solution that may not be suitable for organizations with stringent data sovereignty requirements.
- Integration with SAP ecosystem: If your organization already uses SAP products such as SAP S/4HANA, SAP BW/4HANA, or other SAP applications, choosing SAP HANA for your data warehousing needs can result in better integration and compatibility with your existing landscape.
- Advanced analytics: SAP HANA includes built-in machine learning, predictive analytics, and text analysis capabilities.
- Custom development: SAP HANA provides a more flexible platform for custom development compared to SAP Datasphere. With SAP HANA, you can develop custom applications, stored procedures, and functions using languages like SQL Script and R, allowing you to tailor your data warehousing solution to your specific needs.
- Scalability: SAP HANA can scale horizontally and vertically to accommodate growing data volumes and increasing user demands.
However, SAP Datasphere also offers some advantages, such as ease of use, rapid deployment, and lower total cost of ownership due to its cloud-based nature. It's important to carefully consider your organization's needs and resources when choosing between these two solutions.
Hope this will help you to better understand the pros and cons.
Thanks for such a thorough response. I have some more related questions:
1. In reference to "In-memory capabilities: SAP HANA is an in-memory database designed to process high volumes of data in real-time":
Since the underlying database for SAP Data Warehouse Cloud is SAP HANA Cloud, don't we also have the in-memory capabilities there as well?
2. In reference to "Integration with SAP ecosystem: If your organization already uses SAP products such as SAP S/4HANA, SAP BW/4HANA, or other SAP applications, choosing SAP HANA for your data warehousing needs can result in better integration and compatibility with your existing landscape."
I thought SAP Datasphere already supported such integrations with built-in connectors/data sources?
3. I guess we could take advantage of the best of both worlds (such as advanced analytics, custom development and integration) with a hybrid approach of implementing SQL Data Warehousing within the SAP HANA Cloud database underlying SAP Datasphere (or even separately) and then consuming in Datasphere, right?
the development approach of Datasphere and HANA (Cloud) SQL Datawarehousing are very different.
The Blogpost of my colleague sum up the the key characteristica of HANA SQL Data Warehousing. Stefan was also one of the authors of the HANA SQL Data Warehousing Book.
Thanks for the nice blog.
One question here:
Do we have any practical reference already to use nDSO in HANA SQL DW?
Maybe not directly refer to a 'specific' customer, but general info to indicate the wideness will be good enough.
It's difficult to answer specifically to your question.
I'd suggest you to connect to our internal SAP Customer Reference Platform to get this answered.
Hope this helps.
Thank you for sharing your thoughts on native SAP HANA data warehousing. I completely agree that it is a powerful tool for managing and analyzing large amounts of data. As someone who has worked extensively with SAP HANA, I have seen firsthand how it can help organizations make data-driven decisions and improve their overall business performance.