The continuous processing of streaming data has become an important aspect in many applications. Over the last years a variety of different streaming platforms has been developed and a number of open source frameworks is available for the implementation of streaming applications. In this report, we will survey the landscape of existing streaming platforms. Starting with an overview of the evolving developments in the recent past, we will discuss the requirements of modern streaming architectures and present the ways these are approached by the different frameworks
In recent years, the need for continuous processing and real-time analysis of data streams has incre...
Stream processing is a term that is used widely in the literature to describe a variety of systems. ...
The need for scalable and efficient stream analysis has led to the development of many open-source s...
In the era of big data, an unprecedented amount of data is generated every second. The real time ana...
Stream processing languages and stream processing engines have become more popu-lar as they emerged ...
International audienceRecently, increasingly large amounts of data are generated from a variety of s...
Stream processing languages and stream processing engines have become more popular as they emerged f...
In this tutorial paper we present the results of recent research findings in the area of data stream...
Abstract—In this position paper, we motivate the need for streaming data integration in three main f...
Stream processing is a term that is used widely in the literature to describe a variety of systems. ...
Due to the rise of continuous data-generating applications, analyzing data streams has gained increa...
AbstractReal-time data stream processing technologies play an important role in enabling time-critic...
In recent years the demand of faster data processing and real-time analysis and reporting has grown ...
This White Paper (submitted to STREAM 2016) identifies an approach to integrate streaming data with ...
The development of data stream processing has become one of the key themes in the database and distr...
In recent years, the need for continuous processing and real-time analysis of data streams has incre...
Stream processing is a term that is used widely in the literature to describe a variety of systems. ...
The need for scalable and efficient stream analysis has led to the development of many open-source s...
In the era of big data, an unprecedented amount of data is generated every second. The real time ana...
Stream processing languages and stream processing engines have become more popu-lar as they emerged ...
International audienceRecently, increasingly large amounts of data are generated from a variety of s...
Stream processing languages and stream processing engines have become more popular as they emerged f...
In this tutorial paper we present the results of recent research findings in the area of data stream...
Abstract—In this position paper, we motivate the need for streaming data integration in three main f...
Stream processing is a term that is used widely in the literature to describe a variety of systems. ...
Due to the rise of continuous data-generating applications, analyzing data streams has gained increa...
AbstractReal-time data stream processing technologies play an important role in enabling time-critic...
In recent years the demand of faster data processing and real-time analysis and reporting has grown ...
This White Paper (submitted to STREAM 2016) identifies an approach to integrate streaming data with ...
The development of data stream processing has become one of the key themes in the database and distr...
In recent years, the need for continuous processing and real-time analysis of data streams has incre...
Stream processing is a term that is used widely in the literature to describe a variety of systems. ...
The need for scalable and efficient stream analysis has led to the development of many open-source s...