Hi there 👋

After exploring compute, APIs, and orchestration patterns, this week I’m diving into a topic that underpins them all — data architecture.

In my latest article, I break down the core differences between data warehouses, data lakes, and data streaming — and why most modern systems actually need a bit of each.

Here’s what you’ll find inside:
✅ How warehouses, lakes, and streams differ in purpose and design
✅ When to use each (with real-world use cases)
✅ Common pitfalls — like the dreaded “data swamp”
✅ Example AWS-native stacks for every scenario

Read the full post here:
👉 Data Warehouse vs Data Lake vs Data Streaming

As always, my goal isn’t to pick a winner — it’s to help you make thoughtful, pragmatic choices in complex systems.

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Until next time,
Konstantinos
Thoughtful Architect