[The Data Management Survey 22 results, not included in Data Management Survey 23] SAP was founded in 1972 as a business applications company but really came into prominence in the 1990s with the ERP boom. Its ERP solution (R/3) was first released in 1992. The vendor now employs more than 100,000 people worldwide and had revenues of $27.3 billion in 2020. Today, SAP is one of the largest business software vendors in the world.
SAP’s ERP core business ever was and is about transactional and analytical business data processing. Therefore, a robust, high-performance database in the background is an essential and important component for success. For many years, SAP was bound to partnerships with third-party database vendors such as Oracle, Microsoft and IBM. This led to a number of compromises and disadvantages for SAP. Most importantly, those database technologies were not really optimized for growing and simultaneous transactional and analytical ERP workloads so performance became a regular problem for SAP customers. In addition, the database licensing slice of the revenues did not go to SAP.
SAP started to develop its own database in 2008, led by the Hasso Plattner Institute and Stanford University. In 2010, SAP HANA was launched as an in-memory database and ‘application development platform for the processing of high-volume data in real time’. Originally, SAP HANA was available as an appliance only. It has since evolved over many iterations into a universal data platform that is the data back end for almost all SAP business applications. SAP HANA leverages all the advantages that an in-memory approach can offer, while being 100 percent ACID-compliant (atomicity, consistency, isolation and durability). Today, SAP HANA can be easily installed on standard hardware, and is also available as an ‘Express Edition’, free to use for development and productive use for up to 32 GB of RAM.
SAP HANA follows the columnar data store paradigm and supports industry standards such as structured query language (ANSI SQL/2016 compliant) and multidimensional expressions (MDX), connectivity through ODBC and JDBC interfaces and the use of the statistical programming language R for back-end scripting. APIs and tools are provided that enable IT departments and data experts to create and run custom-built applications on top of HANA. In addition, SAP HANA is well suited for basic machine learning and predictive analytics use cases, as well as spatial data analysis. It also provides text analysis and processing capabilities through dedicated API libraries, if required, also across multiple data sources. The R language integration is of great value here. HANA’s set-up requires large servers or server clusters with a lot of memory (minimum 24 GB, maximum 16 TB per node) to support larger use cases. However, this should not be seen as a big concern as SAP HANA databases are in general much smaller than traditional database architectures, due to high levels of data compression.
SAP HANA is often connected to an SAP System (called ‘SAP HANA Sidecar Setup’) and runs in parallel to a source SAP ERP application, enabling analysts to access real-time operational and transactional data for analytical processing. It is also the default (and recommended) back end for SAP BW, SAP’s business intelligence and data warehouse platform, now known as SAP BW/4HANA.
SAP releases new versions of SAP HANA through Support Package Stacks (SPS), which introduce new features or advancements and bug fixes. In addition to SPS releases, SAP also makes revision versions available that may contain additional features or fixes, and there can be several revisions between each SPS release. In summary, SAP’s release management strategy can be a bit confusing.
It should also be noted that SAP has a huge number of excellent implementation and consulting partners with knowledge of the product portfolio and SAP HANA. Finding highly qualified implementation partners and expertise around the SAP HANA technology is an easy task. This is a huge asset for SAP and SAP HANA.
User & Use Cases
80 percent of our survey respondents use SAP HANA for data warehousing and BI, and only 13 percent use the database for advanced analytics. This is interesting in that we tend to see SAP BW/4HANA used for data warehousing. With SAP BW/4HANA, SAP offers a significantly lower-priced data warehouse application with prebuilt functions and connectors that can also use HANA functions for data warehousing, for example, for data integration. On the other hand, in contrast to SAP BW/4HANA, the HANA database offers support for advanced analytics. Here, however, only 13 percent use the analytical database. In our experience, customers use SAP HANA alongside SAP BW/4HANA in particular when they need more flexible access to data or if they have performance issues. Overall, the spread of tasks shows that SAP HANA is a platform that is able to cover multiple workloads.
The average of 2,522 users suggests that HANA is probably used more operationally, as in the sidecar scenario mentioned above, which also enables ERP users to perform quick analyses, for example. Although there are also some installations outside of the SAP ERP customer group, it is fair to say that SAP HANA is predominately used by SAP ERP customers, which are often larger enterprises, as suggested by the fact that none of the respondents to our survey came from companies with less than 100 employees. If you are an SAP ERP customer, you must have good arguments to not consider SAP HANA as your ‘natural choice’ for data warehousing and analytics too. Overall, the database achieves a high level of penetration within companies as a strategic backbone of SAP products. This is clearly reflected in the figures.
Total number of users per company
Total number of administrators per company
Company size (number of employees)
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