Stream processing systems are pivotal to modern data-driven environments, enabling the continual ingestion, processing and analysis of unbounded data streams across distributed computing resources.
Stream All the Things: Patterns of Effective Data Stream Processing Explored by Adi Polak at QCon SF
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Modern enterprises are hitting scale (>100 million users) at an unprecedented rate. Building applications to retrospectively meet this scale is no longer an option. And scale isn’t just limited to end ...
The de facto standard for real-time stream processing is sometimes described as being complex and difficult to learn. Start by understanding these core principles. In recent years, Apache Flink has ...
On Confluent Cloud for Apache Flink®, snapshot queries combine batch and stream processing to enable AI apps and agents to act on past and present data New private networking and security features ...
At investment management firm Bridgewater Associates Inc., access to real-time data is measured in market ticks. Data feeds containing quote and trade activity are expected to stream in at 124,000 ...
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