
06/07/2025
💥 “We need this to scale to millions of users.”
Me (in 2023): "Sure, let's use MongoDB and hope for the best." 😅
Fast forward to 2025 — I've just finished 4 chapters of Designing Data-Intensive Applications by Martin Kleppmann… and wow. I realize now how little I truly understood about system design, storage engines, or data models back then.
📚 Topics I’ve covered so far:
Relational vs document vs graph databases
B-Trees vs LSM-Trees (and why writes aren’t always cheap)
Encoding formats, schema evolution
The myth of the “perfect database”
🚧 Realization:
👉 I wasn’t solving the wrong problem — I was solving the right problem with the wrong mental model.
What changed?
I now ask “How will this system behave under load?” before I pick tools.
I think about read/write patterns, compaction, data locality
I finally understand what “data-intensive” really means (hint: it's not just about Big Data)
😂 Also, I now laugh nervously whenever I hear:
“Just throw a cache on it.”
✅ Solved problems:
Overfitting tech to hype instead of app needs
Making uninformed storage decisions
Not thinking about data evolution over time
Next up: replication and distributed systems.
Anyone else reading this masterpiece? Or had a “what was I thinking” moment with backend/data architecture?