Posts Tagged

Stream Processing

Data ScienceData Science 101Understanding Big Data

As the scale of data grows across organizations with terabytes and petabytes coming into systems every day, running ad hoc queries across the entire dataset to generate important metrics and intelligence is no longer feasible. Once the quantum of data crosses a threshold, even simple questions such as what is

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Big DataData ScienceData Science 101

This post appeared originally in the dataArtisans blog Six Common Streaming Misconceptions Needless to say, we here at data Artisans spend a lot of time thinking about stream processing. Even cooler: we spend a lot of time helping others think about stream processing and how to apply streaming to data

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News

Apache Samza, the distributed stream processing framework, has now graduated to become a Top-Level Project (TLP), the Apache Software Foundation has revealed. “The incubation process at Apache has been great. It has helped us cultivate a strong community, and provided us with the support and infrastructure to make Samza grow,”

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News

With the advent of Big Data and the rapidly growing scale of web-applications, monolithic relational databases were replaced by scalable, partitioned, NoSQL databases and HDFS; individual queries to relational databases were replaced by the likes of Hive and Pig. This growing scale and partitioned consumption model brought about by these

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