In this episode, we provide an overview of Amazon Aurora, a relational database solution on AWS. We discuss its unique capabilities like distinct storage architecture for better performance and faster recovery. We cover concepts like Aurora clusters, reader and writer instances, endpoints, and global databases. We also compare the serverless versions V1 and V2, noting that V2 is more enterprise-ready while V1 scales to zero. We touch on billing and additional features like the data API, RDS query editor, and RDS proxy. Overall, Aurora is powerful and scalable but not trivial to use at global scale. It's best for serious enterprise use cases or variable traffic workloads.
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🔖 Chapters:
00:00 Intro
00:55 What's the use case for Aurora?
02:26 Overview of Aurora and how it differs from RDS
03:46 Aurora's distinct storage architecture and benefits
06:01 Aurora cluster concepts like instances, endpoints, failover
09:01 Aurora global databases for multi-region replication
12:05 What is Aurora Serverless?
17:39 Comparing Aurora serverless versions V1 and V2
20:12 Billing and cost comparisons of Aurora options
22:11 Additional Aurora features like data API and RDS proxy
26:11 Conclusions and advice on using Aurora
In this episode, we mentioned the following resources:
Amazon Relational Database Service (RDS): https://aws.amazon.com/rds/
Amazon RDS Aurora: https://aws.amazon.com/rds/aurora/
RDS Aurora Serverless: https://aws.amazon.com/rds/aurora/ser...
Cost calculator for cost comparison: https://calculator.aws/#/estimate?id=...
Cloudonaut podcast and blog post about Aurora Serverless V2: https://cloudonaut.io/review-aurora-s...
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