This section explains the features of SAP HANA that make it so special when compared with other in-memory and traditional databases.
For every organization, information is required and acts as an asset to make decisions and run the business. Having the assets doesn't matter, but capitalizing on them remains of high priority. However, delivering this capability to everyone in the organization is impossible. The in-memory computing feature of SAP HANA is a disruptive force that offers speed and swiftness to power analytics at an exceptional performance level while remaining cost effective. To summarize, SAP HANA, built on Intel(R) Xeon(R) Processor 7500 Series, delivers the following features:
Speed and agility: The business commanding for quick change is to create new demands for business and technology. All the data has to be made available to the business users; making sure that no delay occurs on the part of the enterprise data warehouse is critical.
Performance and cost: Advances in hardware and software technologies have improved performance dramatically, without making a huge difference to the maintenance cost. This helps make new computing models.
Different scenarios faced by organizations and how SAP HANA features help organizations find a solution while making tough decisions are discussed here.
Business requirements are very dynamic and highly critical, and there is a need to ensure continuity. Business users and business analysts need to be empowered by having the flexibility to define their views on the information and the application, based on their look and feel, aesthetics, and requirements. The Information Technology Department should strive for business continuity, low redundancy, and the optimal reuse of the systems, information, resources, and infrastructure available.
The move to the SAP in-memory computing engine is a paradigm shift to an innovative foundation that can truly fulfill the promise of real-time analytics and business in the present and future.
Technology has empowered business analytic applications, industry-specific solutions, and functional areas of businesses. Customers need the technological capabilities and empowerment of powerful technology to harness the full potential of data with ease, not only to enable but also to transform various aspects of the business.
The SAP in-memory computing engine, part of SAP HANA, delivers the following capabilities:
A unified database with native support for row and columnar datastores, providing the RDBMS properties, such as atomicity, consistency, isolation, and durability (ACID)
An interface that supports both SQL and Multidimensional Expressions (MDX)
A combined information modeling design environment
Views related to business information are stored in the data repository
Data integration capabilities for accessing both SAP and non-SAP data sources
An integrated LCM—lifecycle management capabilities for transporting and version management capabilities
The capabilities that are mentioned in the preceding list enable the SAP in-memory computing engine to support and process massive amounts of data from heterogeneous data sources in the enterprise; apply complex calculations that are necessary for decision makers to explore and analyze vast amounts of data; and derive actionable insights and information with faster response times, greater flexibility, and much less dependency on the IT team for decision-making.
Business users and stakeholders of organizations can instantly analyze, explore, and access all of their transactional and analytical data in real time from virtually any data source. The data might be operational, analytical, tactical, or strategic in nature, however the in-memory technology allows users to access the previously mentioned types of data in a single snapshot.
External data can be easily integrated or added to analytical models of SAP HANA without going through any cumbersome processes to integrate data from sources of the entire organization.
To outline some general distinctive features and design guidelines and show the key differentiators with respect to common, relational, SQL-based database management systems, the features described in this section represent the cornerstones of the philosophy behind the SAP HANA database.
In order to cope with the requirements of managing enterprise data with different characteristics in different ways, the SAP HANA database comprises a multi-engine query processing environment. In order to support the core features of enterprise applications, the SAP HANA database provides SQL-based access to relationally structured data with full transactional support. Since more and more applications require the enrichment and enhancement of classically structured data with semi-structured, unstructured, or text data, the SAP HANA database provides a text search engine in addition to its classical relational query engine.
The HANA database engine supports the joining of semistructured data to relations in the classical model, in addition to supporting direct entity extraction procedures on semi structured data. Finally, a graph engine, which is a GUI, natively provides the capability to run graph algorithms on networks of data entities to support business applications, such as supply chain optimization, production planning, and social network analyses.
In contrast to classical relational databases, the SAP HANA database is able to provide a deep understanding of the business objects used in the application layer. The SAP HANA database makes it possible to register the semantic models inside the database engine to push down more application semantics into the data management layer. In addition to registering semantically richer data structures (for example, OLAP cubes with measures and dimensions), SAP HANA also provides access to specific business logics implemented directly, deep inside the database engine. The SAP HANA Business Function Library summarizes those application procedures.
Modern data management systems must consider current developments with respect to large amounts of available main memory, the number of cores per node, cluster configurations, and SSD/flash storage characteristics in order to efficiently leverage modern hardware resources and guarantee good query performance at affordable prices. The SAP HANA database is built from the ground up to execute in parallel and main-memory-centric environments. In particular, providing scalable parallelism is the overall design criteria for both the system and application levels.
SAP HANA provides direct connectivity and access to transactional and operational data without disrupting the performance of SAP ERP. Organizations that require business continuity can easily synchronize into memory the key transactional tables that reside in SAP HANA in real time, making these tables easily accessible for business analysis.
SAP HANA can integrate and access any standard data source applicable. In scenarios where organizations require operational or transactional data from non-SAP systems or would like to expand on existing analytic models, any source of data can be used as the foundation for analytics in SAP HANA. Using the SAP BusinessObjects Data Services component, data can be loaded from non-SAP systems into SAP HANA. SAP Data Services is a strategic ETL tool in SAP for heterogeneous sources, data from different sources can be transformed, cleaned, and integrated. This enables us to load data into SAP HANA from different sources. SAP HANA provides an easy-to-use, rich graphical interface, enabling modeling experience to further increase the flexibility in use for business users. Using the semantically enriched information modeling layer of SAP HANA, information views can be created that transform the raw data into relevant and insightful analytical information which helps business users to consume data using SAP BusinessObjects reports, explorer views, and dashboards on the Web or handheld devices (iPad, Android devices, Blackberry, and so on).
Apart from those that we have seen, let's see another feature of SAP HANA.
SAP HANA provides standard interfaces and connectivity to applications, operational systems, and business applications in the current IT landscape. This means that SAP HANA will not disrupt existing landscapes and complements them by connecting to their data sources, leveraging the current investments such as BI clients. The business intelligence and analytical capabilities of SAP BusinessObjects can leverage SAP HANA's in-memory feature as there exists SQL and MDX direct connectivity, and the views created in SAP HANA can be consumed in the SAP BusinessObjects reporting and analytical tools in an easy manner, giving business users a complete, wide range of capabilities for analytics and deriving insightful information. SAP HANA provides different possibilities for users, whether they prefer to use Excel or other tools and applications, via standard interfaces such as MDX or SQL.