@Jatin510

Jagdish Parihar

@Jatin510IndiaJoined April 2021

Software Developer

About

I am software developer, primarily working on the nodejs, graphql, react and mongoDB.

Available for

I am software developer, primarily working on the nodejs, graphql, react and mongoDB.

Jagdish Parihar's blogs

Jatin510 — Database Internals, Rust & Systems Programmingblog.jatin510.dev12 posts

Articles Comments

Recently published

JPJagdish Pariharblog.jatin510.devJul 5 · 9 min read

Connection Pooling Explained: Build One From Scratch in 30 Lines

Nothing is magic — part of a series on building infrastructure primitives from scratch. I used to think request queuing and connection pooling were deep infrastructure magic — something libraries did

JPJagdish Pariharblog.jatin510.devJan 14 · 10 min read

Building PostgreSQL Extensions with Rust: A Complete Guide Using pgrx

Building PostgreSQL Extensions with Rust: A Complete Guide Using pgrx PostgreSQL is one of the most extensible databases ever built. Its extension system lets you add custom data types, functions, operators, and even entirely new storage engines. Tra...

JPJagdish Pariharblog.jatin510.devOct 26, 2025 · 4 min read

I Tried Corrode’s “Prototyping in Rust” — And It Changed How I Build Things

When I came across Corrode’s article on Prototyping in Rust, it immediately clicked with something I’d been struggling with for a while. As someone who builds Rust-based systems every day — from high-throughput analytics pipelines to Web Crawler — I ...

JPJagdish Pariharblog.jatin510.devAug 28, 2025 · 4 min read

My Research Journey into Rust & Performance: Solving the 1BRC Challenge ⚡️

A little over a year ago, I got curious about the 1 Billion Row Challenge (1BRC). It seemed like the perfect playground to test Rust’s performance chops — 1 billion weather station measurements, aggregate per-city statistics (min, max, average), and ...

JPJagdish Pariharblog.jatin510.devAug 5, 2025 · 3 min read

🪶 Apache Arrow: The Modern Memory Format Powering Analytical Engines

Apache 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. ...