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Database scale-out is commonly implemented by partitioning data across several database instances. This approach, however, has several restrictions. In particular, partitioned databases are inflexible in large-scale deployments and assume a partition-friendly workload in order to scale. In this paper, we analyze an alternative architecture design for(More)
Modern data-centric flows in the telecommunications industry require real time analytical processing over a rapidly changing and large dataset. The traditional approach of separating OLTP and OLAP workloads cannot satisfy this requirement. Instead, a new class of integrated solutions for handling hybrid workloads is needed. This paper presents an industrial(More)
Over the years, the HTML-based Web has become a platform for providing applications and dynamic pages that have little resemblance to the collection of static documents it had been in the beginning. This was made possible by the introduction of client-side programmable browsers. Because XML and HTML are cousins, XML technologies can be almost readily(More)
In the last few years, many researchers have come to the conclusion that traditional relational database management systems (RDBMS) can no longer scale to the requirements of today. The traditional setup of RDBMSs relies on having a central processing server which stores all data on disk. We will replace the disk by a distributed storage system which uses(More)
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