What is data consistency in stream processing?
Data consistency in stream processing refers to ensuring that data remains accurate and reliable across distributed systems as it flows in real-time.
Why is data consistency important in real-time applications?
It's crucial because inconsistencies can lead to incorrect decisions, data corruption, and a poor user experience in applications like financial transactions.
What are some common challenges in maintaining data consistency?
Common challenges include handling network failures, managing state across distributed systems, and ensuring timely data updates.
How can we achieve data consistency in stream processing?
Techniques like using distributed consensus algorithms, implementing checkpoints, and leveraging event sourcing can help achieve data consistency.
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