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What role does Kafka play in real-time data streaming pipelines?

Spark/Big Datahard0.4 min readPremium
Frequency
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Asked at 1 company
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452
questions in Spark/Big Data
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88E|81M|283H
in this category
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1,863
across 7 categories
Asked at these companies
BCG
Key Concepts Tested
partitionspark
Expert AnswerPremium
76 wordsInterview-ready
**Roles**: (1) **Durable log**—events persisted; replayable. (2) **Decoupling**—producers and consumers independent. (3) **Buffer**—absorb spikes. (4) **Multiple consumers**—same stream, different use cases. **In Pipelines**: Ingest (clicks, transactions) → Kafka → Spark/Flink process → sink (Delta, DB, dashboard). CDC from DB → Kafka → lake. **Why Kafka**: Throughput (millions/sec), retention, exactly-once (with Transactions API). **Scalability Trade-offs**: Partitions = parallelism....
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