Data Engineering
How to Cut Databricks Compute Costs by 73% Using Job Clusters
What Are Job Clusters? Databricks offers two types of clusters: 1. All-Purpose Clusters — persistent clusters that stay running until you manually terminate them. Great for exploration and ad-hoc analysis, but
Job Clusters vs All-Purpose: The 73% DBU Gap That's Costing You Thousands
## The 73% DBU Gap Nobody Talks About Here's a number that should stop you cold: **all-purpose clusters cost 73% more per DBU than job clusters** in AWS Premium,
The Complete Guide to Databricks Cost Optimization
## The Databricks Cost Problem If you're running Databricks at any scale, you've felt the pain. **The average Databricks customer spends over $300K per year** — and a
Building a Real-Time Trading Analytics Platform with Python and Docker
In this post, we'll walk through the architecture and key design decisions behind a real-time trading analytics platform that processes tick-level market data for multi-asset operations. Architecture Overview
Databricks Delta Lake: Advanced Performance Tuning
Delta Lake brings ACID transactions and schema enforcement to your data lake. But to get the best performance out of it, you need to tune a few knobs. Here'
Understanding Spark Shuffle: A Practical Guide to Optimisation
Spark shuffle is one of the most common sources of performance problems in distributed data processing. In this guide, we'll walk through what shuffle actually is, how to