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GCP for Apache Kafka Users: Stream Ingestion and Processing (Cloud Next '19)
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In private and public clouds, stream analytics commonly means stateless processing systems organized around Apache Kafka or a similar distributed log service. GCP took a somewhat different tack, with Cloud Pub/Sub, Dataflow, and BigQuery, distributing the responsibility for processing among ingestion, processing and database technologies.
We compare the two approaches to data integration and show how Dataflow allows you to join and transform and deliver data streams among on-prem and cloud Kafka clusters, Cloud Pub/Sub topics and a variety of databases. The session will have a mix of architectural discussions and practical code reviews of Dataflow-based pipelines.
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Speaker(s): Ricardo Ferreira, Karthi Thyagarajan
Session ID: DA305
event: Google Cloud Next 2019; re_ty: Publish; product: Cloud - Data Analytics - BigQuery; fullname: Ricardo Ferreira, Karthi Thyagarajan;
We compare the two approaches to data integration and show how Dataflow allows you to join and transform and deliver data streams among on-prem and cloud Kafka clusters, Cloud Pub/Sub topics and a variety of databases. The session will have a mix of architectural discussions and practical code reviews of Dataflow-based pipelines.
Watch more:
Speaker(s): Ricardo Ferreira, Karthi Thyagarajan
Session ID: DA305
event: Google Cloud Next 2019; re_ty: Publish; product: Cloud - Data Analytics - BigQuery; fullname: Ricardo Ferreira, Karthi Thyagarajan;
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GCP for Apache Kafka Users: Stream Ingestion and Processing (Cloud Next '19)
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