From the course: Designing Highly Scalable and Highly Available SQL Databases
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Different data ingestion strategies
From the course: Designing Highly Scalable and Highly Available SQL Databases
Different data ingestion strategies
- [Narrator] Let's take a look at how data is used and how it's different at human scale versus machine scale. By all means this isn't always the case, but typically human scale data is ingested directly by the application which receives the data, writes the data to persistent storage, like a relational database. And typically what we find with things like enterprise applications is that the data is often read a lot more than it's written. So it's a write once read many times kind of scenario. And this data is often used either for targeted look-ups, so, for example, looking up my insurance policy by my account number is one way to do it or by filtering on certain sets of attributes. So for example, you might want to know about sales at a particular region of a particular product. So you filter and query based on those attributes that you're interested in and you get multiple rows back. That's kind of typical for human scale…
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Contents
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Human-scale and machine-scale data6m 13s
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Different data ingestion strategies5m 6s
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Designing scalable user interfaces6m 45s
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Message queues to buffer ingested data4m 10s
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Data modeling for scale: Event sourcing5m 17s
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Distributing workload: Command Query Response Separation (CQSR)4m 26s
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Challenge: Services and APIs for a scable user interface46s
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Solution: Services and APIs for a scable user interface1m 10s
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