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SAP Data Hub 2.3 – What is it and what’s new?

SAP Data Hub is a data orchestration solution that helps enterprises overcome the constraints of a complex data landscape. SAP Data Hub helps to deliver new insights quickly and leads to the creation of innovative data applications by helping data move more easily across the various different sources of the landscape, and by creating data pipelines that leverage a variety of data sources and data processing technologies. The latest version of SAP Data Hub, just announced at SAP TechEd Las Vegas 2018, makes it easier than ever for more people to get value quickly from data.  This new version of SAP Data Hub has improvements to the user experience, is applicable to more cloud data environments, and has an improved, unified data catalog. It also has enhanced connectivity to a broad range of data sources and deeper connections to critical SAP applications, such as S/4 HANA and SAP Hybris.

SAP Cloud Platform Big Data Services

SAP’s cloud Big Data solution is SAP Cloud Platform Big Data Services (BDS). Based on Hadoop and Spark, the Big Data services solution stands out for its scalability and performance, especially since it includes operations services with every subscription. This means that in addition to the typical server and software management, data operations for Big Data management and processing are handled for you, to ensure the highest level of data processing effectiveness and efficiency over time. The result is that you avoid the headaches of Big Data operations management and instead get consistent and reliable high performance.

Weaving the Enterprise Data Fabric

In combination, SAP Data Hub and SAP Cloud Platform Big Data Services make it easy for an enterprise to achieve an effective data fabric architecture for their organization.  SAP Data Hub provides the critical data orchestration and cross-source pipelining capabilities, while Big Data Services provides a high-performance data lake.

A data fabric allows an organization to manage, process, and analyze disparate sources and types of data, as well as deliver that information and analytics broadly throughout the organization. This data can be held, for example, in on-premises databases and data warehouses, in cloud storage, or in cloud or on-premises Big Data solutions. The fabric can also connect to applications, either as a data source point or as an endpoint for processed data or analytics. The data fabric lays the foundation for companies to become intelligent enterprises – an organization in which the right information is delivered at the right time and to the right endpoint, providing the best possible product or service to the end customer.


Creating a Data Fabric with SAP Data Hub and SAP Cloud Platform Big Data Services

SAP Cloud Platform Big Data Services can serve as a high-performance, high-reliability cloud data lake serving the overall data fabric that is managed by SAP Data Hub.

What’s new together?

With SAP Data Hub 2.3 and the latest version of SAP Cloud Platform Big Data Services (to be released in Q4 2018), the integration between the two solutions is easier to implement and more robust. Key new capabilities include:

  • Easier integration Previously, a VPN was required to connect SAP Data Hub and BDS. With the latest version of both solutions, a VPN is no longer required. This makes it easier and lower cost to integrate the two solutions, while still ensuring a secure, high-performance data connection. This easier integration applies not only to Data Hub on-premises, but also Data Hub available in the cloud on AWS and Google Cloud.

  • Spark processing execution in BDS via Data Hub pipelines In addition to the HDFS and HIVE capabilities that were already exposed between the two solutions, customers will also have the ability to run Spark jobs on SAP Cloud Platform Big Data Services via data pipelines in SAP Data Hub. This means that fast analytics on the data held in SAP Cloud Platform Big Data Services can be easily invoked and consumed from the user-friendly SAP Data Hub cockpit.


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