Apache Kafka's Tiered Storage revolutionizes real-time data streaming by enabling the separation of data into two tiers: hot, local storage for recent data and cheap cloud object storage for historical data. This innovation allows developers to retain more historical data while reducing storage costs, alleviating the traditional dilemma between cost and retention. Conversations with experts like Anil Inamdar highlight practical implementations and potential challenges, making Tiered Storage an enticing option for teams looking to enhance Kafka's capabilities in mission-critical applications.
Kafka's Tiered Storage completely flips this model. Instead of keeping everything on expensive local disks, Kafka now separates your data into two distinct tiers.
If you've ever wrestled with retention of messages in Kafka, this can be a game-changer. It allows developers to optimize both cost and performance without sacrificing historical data.
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