A DBMS prototype to support extended NF2 relations: an integrated view on flat tables and hierarchies

Dadam, Peter; Kuespert, K.; Andersen, F.; Blanken, H.; Erbe, R.

doi:10.1145/16894.16889

Cited by 98 publications

(22 citation statements)

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“…References to other tuples can be expressed through queries (i.e., the data type postquel), but otherwise ADTs, and their associated relations, still had to be in first normal form. This restriction was relaxed in systems that have a more powerful type system (e.g., an OO data model) [10,35,41,74,93]. Another area in which extensions have been extensively considered are index structures.…”

Section: Oodbms: Relaxing Data Management and Program Independencementioning

confidence: 99%

Big Data Management: What to Keep from the Past to Face Future Challenges?

2017

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The emergence of new hardware architectures, and the continuous production of data open new challenges for data management. It is no longer pertinent to reason with respect to a predefined set of resources (i.e., computing, storage and main memory). Instead, it is necessary to design data processing algorithms and processes considering unlimited resources via the ''pay-as-you-go'' model. According to this model, resources provision must consider the economic cost of the processes versus the use and parallel exploitation of available computing resources. In consequence, new methodologies, algorithms and tools for querying, deploying and programming data management functions have to be provided in scalable and elastic architectures that can cope with the characteristics of Big Data aware systems (intelligent systems, decision making, virtual environments, smart cities, drug personalization). These functions, must respect QoS properties (e.g., security, reliability, fault tolerance, dynamic evolution and adaptability) and behavior properties (e.g., transactional execution) according to application requirements. Mature and novel system architectures propose models and mechanisms for adding these properties to new efficient data management and processing functions delivered as services. This paper gives an overview of the different architectures in which efficient data management functions can be delivered for addressing Big Data processing challenges.

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Section: Oodbms: Relaxing Data Management and Program Independencementioning

confidence: 99%

Big Data Management: What to Keep from the Past to Face Future Challenges?

2017

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“…Advanced database systems such as object oriented (Maier et al, 1986;Woelk et al, 1986;Weinreb et al, 1988) and extended relational (Stonebraker, 1986;Schwarz et al, 1986;Dadam et al, 1986) provide many of the facilities of HyperFile (objects, pointers, queries), but also provide a lot more (like a full programming language or an inferencing engine). As discussed in the Introduction, HyperFile is likely to be a "value added system" on top of an advanced object oriented storage system.…”

Section: Advanced Database Systemsmentioning

confidence: 99%

HyperFile: A data and query model for documents

Clifton

García-Molina

Bloom³

1995

VLDB Journal

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Abstract. Non-quantitative information such as documents and pictures pose interesting new problems in the database world. Traditional data models and query languages do not provide appropriate support for this information. Such data are typically stored in file systems, which do not provide the security, integrity, or query features of database management systems. The hypertext model has emerged as a good interface to this information; however, finding information using hypertext browsing does not scale well. We developed a query interface that serves as an extension of the browsing model of hypertext systems. These queries minimize the repeated user interactions required to locate data in a standard hypertext system. HyperFile is a prototype data server interface. In this article, we describe HyperFile, including a number of issues such as query generation, query processing, and indexing.

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“…A consequence of these requirements, observations, and ideas is the so-called DBMS kernel architecture [2,7,15], as illustrated in Fig. 6.…”

Section: Overview Of the System Architecturementioning

confidence: 99%

Processing and transaction concepts for cooperation of engineering workstations and a database server

Häder

Hübel

Meyer-Wegener

et al. 1988

Data & Knowledge Engineering

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Abstract. A DBMS kernel architecture is proposed for improved DB support of engineering applications running on a cluster of workstations. Using such an approach, part of the DBMS codeman applicationspecific layermis allocated close to the corresponding application on a workstation while the kernel code is executed on a central server. Empirical performance results from DB-based engineering applications are reported to justify the chosen DBMS architecture.The paper focuses on design issues of the application layer including server coupling, processing model and application interface. Moreover, a transaction model for long-term database work in a coupled workstationserver environment is investigated in detail.

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A DBMS prototype to support extended NF2 relations: an integrated view on flat tables and hierarchies

Cited by 98 publications

References 0 publications

Big Data Management: What to Keep from the Past to Face Future Challenges?

Big Data Management: What to Keep from the Past to Face Future Challenges?

HyperFile: A data and query model for documents

Processing and transaction concepts for cooperation of engineering workstations and a database server

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