The Web of Data is an open environment consisting of very large, inter-linked RDF datasets from various domains (e.g., DBpedia, GeoNames, ACM, PubMed, etc.) accessed through SPARQL queries. Establishing interoperability in this environment has become a ...

The emergence of mobile and ambient computing technologies brings democratization in the access to information and data; services play a crucial role, thereby opening new research challenges for data querying. A promising method to access data within ...

The recent growth of non-relational databases (often termed as NoSQL) is an interesting phenomenon that has generated both interest and criticism. One of the major drawbacks that is often referred to is the heterogeneity of the languages and interfaces ...

One of the leading challenges for pervasive computing is to ease the application development to smoothly handle the surrounding environment. We consider the case where the environment produces heterogeneous and continuous data, e. g. temperature ...

Physical design represents one of the hardest problems for database management systems. Without proper tuning, systems cannot achieve good performance. Offline indexing creates indexes a priori assuming good workload knowledge and idle time. More ...

During the last decade, data management and storage have become increasingly distributed. In consideration of the huge amount of data available in such systems, advanced query operators, such as skyline queries, are necessary to help users process the ...

Supporting online transaction processing (OLTP) workload in a scalable and elastic fashion is a challenging task. With the advent of cloud-based systems, supporting entity group based consistency is a viable, scalable, and cost-effective option. This ...

We present some architectural and technological insights on SAP's HANA database and derive research challenges for future enterprise application development.

The HANA database management system [1] was developed to meet changed requirements of modern ...

General-purpose streaming systems support diverse application domains with powerful and user-defined stream operators. Most general-purpose streaming systems have their own, non-XML, internal data representation. However, streaming input is often either ...

Database engines often consume significant power during query processing activities, motivating researchers to investigate the redesign of their internals to minimize these overheads. While the prior literature has dealt exclusively with average power ...

Cloud-based data management platforms often employ multitenant databases, where service providers achieve economies of scale by consolidating multiple tenants on shared servers. In such database systems, a key functionality for service providers is ...

We propose new adaptive runtime techniques for MapReduce that improve performance and simplify job tuning. We implement these techniques by breaking a key assumption of MapReduce that mappers run in isolation. Instead, our mappers communicate through a ...

Summarizability in a multidimensional (MD) database refers to the correct reusability of pre-computed aggregate queries (or views) when computing higher-level aggregations or roll-ups. A dimension instance has this property if and only if it is strict ...

The inherent flexibility of the RDF data model has led to its notable adoption in many domains, especially in the area of life-sciences. Some of these domains have an emerging need to access data integrated from various distributed sources of ...

Query optimization in RDF Stores is a challenging problem as SPARQL queries typically contain many more joins than equivalent relational plans, and hence lead to a large join order search space. In such cases, cost-based query optimization often is not ...

Efficient processing of skyline queries has been an area of growing interest. Most existing techniques assume that the skyline query is applied to a single data table. Unfortunately, this is not true in many applications where, due to the complexity of ...

Given a multi-features data set, a best preference query (BPQ) computes the maximal preference score (MPS) that the tuples in the data set can achieve with respect to a preference function. BPQs are very useful in applications where users want to ...

With the explosion of information stored world-wide, data intensive computing has emerged as a central area of research. Efficient management and processing of this massively exponential amount of data from diverse sources, such as telecommunication ...

Many stream processing applications require access to a multitude of streaming as well as stored data sources. Yet there is no clear semantics for correct continuous query execution over these data sources in the face of concurrent access and failures. ...

With the popularization of GPS-enabled devices there is an increasing interest for location-based queries. In this context, one interesting problem is processing top-k spatial keyword queries. Given a set of objects with a textual description (e.g., ...