# PostgreSQL Indexing: When BRIN Beats B-Tree

### Summary:

If you're dealing with **huge tables** and struggling with **B-Tree index bloat** or slow bulk inserts, it's time to look at **BRIN (Block Range Indexes)**.

This article explains:

**What BRIN indexes are** and how they work internally  
**How they compare to B-Tree indexes** in terms of size, performance, and maintenance  
When BRIN is a **better choice**, especially for:

* Time-series or append-only data
    
* Huge, cold partitions
    
* Queries filtering by time or sequential IDs
    

### Key Takeaways:

* BRIN indexes are **tiny** and **fast to build**, ideal for large tables.
    
* They're **not a B-Tree replacement**, but a powerful companion in the right scenarios.
    
* Proper **data ordering** makes or breaks BRIN performance.
    
* Combine BRIN (e.g., on timestamps) with B-Tree (e.g., on IDs) for best results.
    

Check this post here: [https://kiransabne.dev/postgresql-indexing-when-brin-is-a-better-choice-than-b-tree](https://kiransabne.dev/postgresql-indexing-when-brin-is-a-better-choice-than-b-tree)