Write-Ahead Log Explained: Build Crash-Safe Durability in 30 LinesLast time we built a connection pool from scratch. This time: how does a database not lose your data when the power dies? You write a row. The database says OK. A millisecond later, someone trips oveJul 26, 2026·17 min read
🪶 Apache Arrow: The Modern Memory Format Powering Analytical EnginesApache Arrow is an in-memory columnar data format optimized for analytical workloads. It enables fast data access, zero-copy reads, and efficient interoperability between systems like Pandas, DuckDB, Polars, and query engines like Apache DataFusion. ...Aug 5, 2025·3 min read
Understanding Parquet: An Efficient Columnar File FormatIntroduction Parquet has quickly become one of the most popular file formats for storing large-scale analytics data. Parquet is now a top choice due to its efficiency, compression, and seamless integration with big data frameworks. My experience cont...Jul 24, 2025·2 min read
My Journey into Query Engines, Databases, and Rust🚀 Introduction My journey into query engines, databases, and Rust began with curiosity and a passion for systems-level performance. Rust's promise of safety and efficiency drew me in, while databases provided the perfect playground to test its capab...Jul 19, 2025·3 min read
Implementing `simplify` for `starts_with` in Apache DataFusionIntro about Datafusion Apache DataFusion is a Rust-native query engine with a powerful optimizer. One key component of its optimizer is expression simplification, often referred to as the simplify function. In this post, we'll walk through how we imp...Mar 1, 2025·7 min read
Implementing Custom API timeout using the `Promise.race()` method.This article demonstrates the implementation of Promise.race() method.Sep 14, 2022·2 min read
