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Beyond Enterprise Data Lineage: The Case for a Platform-Independent Data Catalog

Most organizations start their data governance journey by asking how to track where data comes from and where it goes. They quickly discover a harder question: why can none of their existing tools answer that across all systems? Vendor-specific lineage tools like Confluent, Snowflake Horizon, and Databricks Unity Catalog each do a good job within their platform boundary. The problem is the boundary. Enterprise-wide lineage requires a platform-independent catalog layer that integrates everything and is owned by none of the platforms it connects.
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Durable Execution Engine with Restate Temporal DBOS vs Stream Processing with Kafka Streams Apache Flink Spark Structured Streaming
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­­The Rise of the Durable Execution Engine (Temporal, Restate) in an Event-driven Architecture (Apache Kafka)

Durable execution engines like Temporal and Restate are redefining how developers orchestrate long-running, stateful workflows in distributed systems. Unlike traditional BPM tools focused on human-centric tasks, these engines automate machine-to-machine processes with built-in durability, retries, and fault-tolerant coordination. When integrated with event-driven platforms like Apache Kafka, they enable scalable, resilient architectures—handling complex business logic such as order processing, fraud detection, and multi-step transactions. This blog explores their capabilities, differences from stream processing tools like Apache Flink, Kafka Streams or Spark Structured Streaming, and the emerging role they play in modern enterprise infrastructure.
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