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Global Field CTO | Author | International Speaker | Follow me with Data in Motion

Comparing #ApacheFlink and #ApacheSpark for Modern #StreamProcessing => Detailed comparison of these two #opensource frameworks by our friends from Decodable... The comparison includes: - Architectural design - (Stateful) stream processing capabilities - Production readiness https://lnkd.in/ecqp2eeW

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Chitrang D.

Data + Analytics + AI + Technology in Healthcare & Life Sciences | Chief Data and Analytics Officer | Growth, Innovation, and Efficiency

6d

Great work by Decodable. Thanks for sharing Kai. Im bookmarking. IMO, Spark’s micro-batch first is still batch vs Flink’s streaming. 🍎|🍊

Patrick Scheblein

Head of Workplace | #erfolgreichmacher | #proudtobeenthus

6d

Thank you for sharing this insightful comparison.

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Vishwajeet Dabholkar

Solutions Engineer| Prompt Engineer| GenAI | VectorsDBs | RAG Applications | LLM applicatios | Data Engineer | Python | PySpark | SQL | SingleStore Database |AWS | Databricks | Azure | REST API | Ex-TCS | Ex-Lumiq.ai

6d

Thanks for sharing

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Adriaan Zeeman

Staff Software Engineer at JUMO

6d

This is great, Kai! Thanks for sharing.

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Wessim Slimi ,

AWS Certified® Data Cloud Engineer Spark, Flink, Kafka, Iceberg

6d

Great advice

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