From the course: Designing Highly Scalable and Highly Available SQL Databases

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Solution: Revised database architecture

Solution: Revised database architecture

From the course: Designing Highly Scalable and Highly Available SQL Databases

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Solution: Revised database architecture

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(lively music) - [Instructor] Okay, this solution identifies two changes we would make. The first thing we want to focus on is the fact that time series data and user-generated data are really distinct. They have different life cycles, different patterns, different volumes, so they should not be going to the same endpoint. Time series data should be ingested using some kind of buffering mechanism, for example, using Apache Kafka or Google Cloud Pub/Sub, something to buffer that data, whereas user-generated data is small enough volume that it can be handled by simply calling APIs, which directly work with the database. Now, the second change is around the analytical queries. Now, analytical queries are really different from transaction processing queries. So we have separate designs for those, separate schemas. And it may even be in different database servers, depending on what kind of databases you're using. For…

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