How can I ensure scalability in my data pipeline tools?
An example of an AI chatbot conversation about scalability in data pipeline tools.
How can I ensure scalability in my data pipeline tools?
To ensure scalability, choose tools that can handle increased data loads and support distributed processing.
What are some popular tools that offer scalability?
Popular tools include Apache Kafka, Apache Spark, and AWS Glue, all designed for scalable data processing.
How do I decide which tool is best for my needs?
Consider factors like data volume, processing speed, integration capabilities, and your team's expertise.
Can you explain the difference between batch and stream processing?
Batch processing handles large volumes of data at once, while stream processing deals with data in real-time as it arrives.
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