Data Management
Using data management products and technologies from SAP, you can record, manage and process massive amounts of data to capture real-time insights.
SAP HANA lets you develop sophisticated apps using hybrid transactional and analytical processing features. It also provides a broad set of advanced analytics (text, predictive, spatial, graph, streaming, and time series).
SAP HANA Cloud lets you manage data from different sources, get real-time insights, and run powerful apps all within a single cloud solution. You can deploy it as a stand-alone solution, or as an extension to your existing on-premise environment.
SAP Data Intelligence enables you to orchestrate distributed data, while re-using existing code and distributed processing engines.
Under the Hood
Data management products and technologies from SAP give a range of users the power to leverage data. Business users can mash up enterprise data with data from their own files to uncover insights. Data analysts can dig deeper into SAP HANA data marts to assess current, historical and predictive data that can be used to optimize operations. Data engineers can build and run data pipelines that produce new value from multiple, diverse data stores -- on-premise and in the cloud, inside and outside the organization. Data scientists can build and maintain models for use in their organization’s data-driven services.
Related Products
SAP HANA
SAP HANA is a complete database and application development platform; it combines an ACID-compliant database with high-speed analytics, application services and flexible data-acquisition tools.
SAP HANA, express edition
SAP HANA, express edition is a streamlined version of SAP HANA that can run on laptops and other resource-constrained hosts. The express edition is free to use for in-memory databases up to 32GB of RAM. Memory capacity increases beyond 32GB are available for purchase in the SAP Store.
SAP Data Intelligence
SAP Data Intelligence orchestrates all your data so you can transform structured, unstructured, and streaming data into business insights. It runs on Kubernetes using Docker containers. Create pipelines and data workflows. Govern data that is focused on metadata catalog and data preparation. In addition, you can use machine learning to create and deploy ML models.