Big Data analytics has recently gained increasing popularity as a tool to process large
amounts of data on-demand. Spark and Flink are two Apache-hosted data analytics …

We live in an age of so-called Big Data. The radical expansion and integration of
computation, networking, digital devices, and data storage have provided a robust platform …

Batched stream processing is a new distributed data processing paradigm that models
recurring batch computations on incrementally bulk-appended data streams. The model is …

With the increasing volumes of information gathered via patient monitoring systems,
physicians have been put on increasing pressure for making sophisticated analytical …

Hadoop and Spark are widely used distributed processing frameworks for large-scale data
processing in an efficient and fault-tolerant manner on private or public clouds. These big …

Context: Data-intensive systems, aka big data systems (BDS), are software systems that
handle a large volume of data in the presence of performance quality attributes, such as …

Recently there has been a significant interest in building big data analytics systems that can
handle both" big data" and" fast data". Our work is strongly motivated by recent real-world …

This paper presents our joint research efforts on big data benchmarking with several
industrial partners. Considering the complexity, diversity, workload churns, and rapid …

Big data is data that exceeds the processing capacity of conventional database systems.
The data is too big, moves too fast, or doesn't fit the strictures of your database architectures …

Big data is a potential research area receiving considerable attention from academia and IT
communities. In the digital world, the amounts of data generated and stored have expanded …