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| Aurora Deep Dive Series by Rathish Kumar - Part 1 |
Scaling a database sounds simple—until you're staring down a production outage.
The reality is that for decades, the very design of our databases has been at odds with the demands of modern, high-growth applications.
Most traditional database systems begin with a monolithic architecture. In this model, everything—compute, memory, and storage—is tightly coupled and resides on a single server. This all-in-one approach is straightforward when you're starting small. But as your traffic and data volumes explode, that single server inevitably becomes a bottleneck. The first, most common response is to scale vertically by upgrading to a bigger, more powerful server. However, this strategy quickly runs into hard physical and cost limitations. Moreover, you're left with a critical single point of failure, where one hardware issue can bring your entire application to a halt.
Most traditional database systems begin with a monolithic architecture. In this model, everything—compute, memory, and storage—is tightly coupled and resides on a single server. This all-in-one approach is straightforward when you're starting small. But as your traffic and data volumes explode, that single server inevitably becomes a bottleneck. The first, most common response is to scale vertically by upgrading to a bigger, more powerful server. However, this strategy quickly runs into hard physical and cost limitations. Moreover, you're left with a critical single point of failure, where one hardware issue can bring your entire application to a halt.
