Christof Bornhövd

SAP HANA database: data management for modern business applications

The SAP HANA database is positioned as the core of the SAP HANA Appliance to support complex business analytical processes in combination with transactionally consistent operational workloads. Within this paper, we outline the basic characteristics of the SAP HANA database, emphasizing the distinctive features that differentiate the SAP HANA database from other classical relational database management systems. On the technical side, the SAP HANA database consists of multiple data processing engines with a distributed query processing environment to provide the full spectrum of data processing -- from classical relational data supporting both row- and column-oriented physical representations in a hybrid engine, to graph and text processing for semi- and unstructured data management within the same system. From a more application-oriented perspective, we outline the specific support provided by the SAP HANA database of multiple domain-specific languages with a built-in set of natively implemented business functions. SQL -- as the lingua franca for relational database systems -- can no longer be considered to meet all requirements of modern applications, which demand the tight interaction with the data management layer. Therefore, the SAP HANA database permits the exchange of application semantics with the underlying data management platform that can be exploited to increase query expressiveness and to reduce the number of individual application-to-database round trips.

Integrating automatic data acquisition with business processes experiences with SAP's auto-ID infrastructure

Smart item technologies, like RFID and sensor networks, are considered to be the next big step in business process automation [1]. Through automatic and real-time data acquisition, these technologies can benefit a great variety of industries by improving the efficiency of their operations. SAPs Auto-ID infrastructure enables the integration of RFID and sensor technologies with existing business processes. In this paper we give an overview of the existing infrastructure, discuss lessons learned from successful customer pilots, and point out some of the open research issues.

Efficient transaction processing in SAP HANA database: the end of a column store myth

The SAP HANA database is the core of SAPs new data management platform. The overall goal of the SAP HANA database is to provide a generic but powerful system for different query scenarios, both transactional and analytical, on the same data representation within a highly scalable execution environment. Within this paper, we highlight the main features that differentiate the SAP HANA database from classical relational database engines. Therefore, we outline the general architecture and design criteria of the SAP HANA in a first step. In a second step, we challenge the common belief that column store data structures are only superior in analytical workloads and not well suited for transactional workloads. We outline the concept of record life cycle management to use different storage formats for the different stages of a record. We not only discuss the general concept but also dive into some of the details of how to efficiently propagate records through their life cycle and moving database entries from write-optimized to read-optimized storage formats. In summary, the paper aims at illustrating how the SAP HANA database is able to efficiently work in analytical as well as transactional workload environments.

Integrating Smart Items with Business Processes An Experience Report

Smart item technologies, like RFID and sensor networks, are considered to be the next big step in business process automation. Through automatic and real-time data acquisition, these technologies can benefit a great variety of industries by improving the efficiency of their operations. SAPs Auto-ID infrastructure enables the integration of RFID and sensor technologies with existing business processes. In this paper we give an overview of the existing infrastructure, discuss lessons learned from successful customer pilots, and point out some of the open research issues.

DREAM: Distributed Reliable Event-Based Application Management

New applications and the convergence of technologies, ranging from sensor networks to ubiquitous computing and from autonomic systems to event-driven supply chain management, require new middleware platforms that support proactive event notification. We present a system overview and discuss the principles of Dream, a reactive middleware platform that integrates event detection and composition mechanisms in a highly distributed environment; fault-tolerant and scalable event notification that exploits a variety of filter placement strategies; content-based notification to formulate powerful filters and concept-based notification to extend content-based filtering to heterogeneous environments; middleware-mediated transactions that integrate notifications and transactions; and scopes, which are administration primitives for both deployment- and runtime configurability, as well as for the management of policies. We discuss four prototypes that were implemented as proof-of-concept systems and present lessons learned from them.

CREAM: An Infrastructure for Distributed, Heterogeneous Event-Based Applications

Applications ranging from event-based supply chain management to enterprise application integration and pervasive computing depend on the timely detection and notification of events. We present Cream the event-based reactive component of the Dream middleware platform. Here we address four key issues in distributed and heterogeneous environments: event detection and notification, event composition, an active functionality service, and ontology support. We show the need for ontology support at all levels in heterogeneous environments and present a distributed active functionality service that addresses the difficult issues of event composition in widely distributed environments. We illustrate the practicality of the proposed approach through two prototypes that are based on this infrastructure: a meta-auction service and a personalized service offering in Internet-enabled vehicles.

Moving Active Functionality from Centralized to Open Distributed Heterogeneous Environments

Active functionality is especially useful for enforcing business rules in applications, such as Enterprise Application Integration (EAI) and e-commerce. It can be used as glue among existing applications, and for data transformations between heterogeneous applications. However, traditional active mechanisms have been designed for centralized systems and are monolithic, thus making it difficult to extend and adapt them to the requirements imposed by distributed, heterogeneous environments. To correct this we present a flexible, extensible, service-based architecture built on ontologies, services and events/notifications. The main contributions of this work are: i) the homogeneous use of ontologies for a semantically meaningful exchange and combination of events in open heterogeneous environments, and for the infrastructure itself; ii) a flexible architecture for the composition of autonomous, elementary services to provide Event-Condition-Action (ECA) functionality in different configurations; iii) the interaction of these services via notifications using a publish/subscribe mechanism (concept-based addressing).

DBCache: middle-tier database caching for highly scalable e-business architectures

Multi-tier infrastructures have become common practice for implementing high volume web sites. Such infrastructures typically contain TCP load balancers, HTTP servers, application servers, transaction-processing monitors, and databases. Caching has been widely used at different layers of the infrastructure stack to improve scalability and response time of e-business applications. The majority of existing caching mechanisms target only static HTML pages or page fragments. However, as web applications become more dynamic through increased personalization, these caching techniques turn out to be less useful. Consequently, as more application requests result in increased querying and updating of backend database servers, scalability limits are often reached.

A Prototype for Metadata-Based Integration of Internet Sources

The combination of semistructured data from different sources on the Internet often fails because of syntactic and semantic differences. The resolution of these heterogeneities requires explicit context information in the form of metadata. We give a short overview of a representation model that is well suited for the explicit description of semistructured data, and show how it is used as the basis of a prototype for metadata-driven integration of heterogeneous data extracted from Web-pages.

Semantic metadata for the integration of Web-based data for electronic commerce

Today, the Internet can be seen as a global marketplace populated by a huge number of providers and consumers that exchange data from a wide range of domains. A combination of data from different sources for further automatic processing is often hindered by differences in the underlying modeling assumptions and representation. In addition, the available sources are in most cases semistructured, i.e., provide no fixed and explicitly specified schema. Therefore, an integrated use of Web-based data requires explicit information about its organization and meaning. In this paper we present a representation model well-suited for explicit description of implicitly described semistructured data, and show how this model can be used for the integration of heterogeneous data sources from the Web.Today, the Internet can be seen as a global marketplace populated by a huge number of providers and consumers that exchange data from a wide range of domains. A combination of data from different sources for further automatic processing is often hindered by differences in the underlying modeling assumptions and representation. In addition, the available sources are in most cases semistructured, i.e., provide no fixed and explicitly specified schema. Therefore, an integrated use of Web-based data requires explicit information about its organization and meaning. In this paper we present a representation model well-suited for explicit description of implicitly described semistructured data, and show how this model can be used for the integration of heterogeneous data sources from the Web.