The first edition of this book appeared in 1991 when the technology was new and there were
not too many products. In the Preface to the first edition, we had quoted Michael Stonebraker …

Since the late 1970s, relational database technology has been adopted by most
organizations to store their essential data. However, nowadays, the needs of these …

The inevitability of the relationship between big data and distributed systems is indicated by
the fact that data characteristics cannot be easily handled by a standalone centric approach …

Building cloud data-intensive applications often requires using multiple data stores (NoSQL,
HDFS, RDBMS, etc.), each optimised for one kind of data and tasks. However, the wide …

With the growing amount of data being continuously produced, it is crucial to come up with
solutions to expose data from ever more heterogeneous databases (eg NoSQL systems) as …

The last two decades witnessed a remarkable evolution in terms of data formats, modalities,
and storage capabilities. Instead of having to adapt one's application needs to the, earlier …

Digital data is a gold mine for modern journalism. However, datasets which interest
journalists are extremely heterogeneous, ranging from highly structured (relational …

The blooming of different cloud data management infrastructures has turned multistore
systems to a major topic in the nowadays cloud landscape. In this demonstration, we present …

The recent successes of commercial cognitive and AI applications have cast a spotlight on
knowledge graphs and the benefits of consuming structured semantic data. Today …

The increasing popularity of NoSQL systems has lead to the model of polyglot persistence,
in which several data management systems with different data models are used. Data lakes …