Data in the emerging world of stream processing


This guest post comes from Neha Narkhede, co-founder and CTO at Confluent, a startup focused on Apache Kafka and founded by its creators. Data systems in the modern world aren't islands that stand on their own; data often flows between databases, offline data stores and search systems, as well as to stream processing systems. But for a long time, data technology in companies was fairly homogeneous; data mostly resided in two popular locations: operational data stores and the data warehouse. And a substantial portion of data collection and processing that companies did ran as big batch jobs -- CSV files dumped out of databases, log files collected at the end of the day, etc. But businesses operate in real time and the software they run is catching up.

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