ETL is dying. Not slowly, not quietly, but in a spectacular blaze of irrelevance that most people haven’t noticed yet.
I know that sounds dramatic. ETL has been the backbone of data processing for thirty years. Every data pipeline you’ve ever built probably follows the extract-transform-load pattern. But here’s the thing: the world has changed faster than our tooling, and ETL is about to become as obsolete as punch cards.
Don’t believe me? Let me show you what’s coming next.
The Perfect Storm Killing ETL
Three massive shifts are converging to make traditional ETL architectures obsolete:1. The Data Volume Explosion: We generated 149 zettabytes of data in 2024. That’s 138 trillion gigabytes. Traditional ETL batch processing can’t keep up with this volume.
2. The Real-Time Imperative: Users expect live data. When someone posts on social media, ads need to update instantly. When a payment processes, fraud detection runs immediately. Batch jobs that run nightly feel ancient.
3. The AI Revolution: AI models need continuous streams of training data, not historical snapshots. The old “extract, batch process, load” cycle is fundamentally incompatible with how…
The End of ETL: The Radical Shift in Data Processing That’s Coming Next
ETL is dying. Not slowly, not quietly, but in a spectacular blaze of irrelevance that most people haven’t noticed yet.
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