Apache Kafka is preferred for high-throughput streaming use cases that require low-latency processing and fault tolerance. It's ideal when you have multiple consumers that need to access the same data stream, or when data needs to be processed in real-time across various systems. For example, in a financial services application where you need to process and analyze stock market data in near real-time, Kafka would be a better choice than Flume due to its ability to handle high volumes of data and provide immediate insights.
Apache Flume is ideal for scenarios where you need to collect, aggregate, and transfer log data from multiple sources to a centralized data store, particularly in a Hadoop ecosystem. Use Flume when your primary goal is to ingest logs from different services efficiently without complex configurations, such as streaming web server logs into HDFS for analysis.