What Spark’s Structured Streaming really means

Thanks to an impressive grab bag of improvements in version 2.0, Spark’s quasi-streaming solution has become more powerful and easier to manage

Last year was a banner year for Spark. Big names like Cloudera and IBM jumped on the bandwagon, companies like Uber and Netflix rolled out major deployments, and Databricks’ aggressive release schedule brought a brace of improvements and new features. Yet real competition for Spark also emerged, led by Apache Flink and Google Cloud Dataflow (aka Apache Beam).

Author: Ian Pointer

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