Write-Optimized Index Structures, Bitmap Indices, and PostgreSQL

#database #indexing #postgres #lsmtree

Tags: #SnowTech #Databases #Indexing #LSMTrees #BitmapIndex #SpatialIndexing #TemporalIndexing #PostgreSQL

Difficulty: Advanced

Reading Time: 45 min read

Last Updated: September 01, 2025

⚡ Beyond B+-Trees: Write-Optimized Index Structures, Bitmap Indices, and PostgreSQL

Databases live and die by their ability to access data efficiently. For decades, the B+-tree was the unquestioned king of indexing, and hash tables powered countless equality lookups. But the world has changed:

Streaming systems generate millions of inserts per second.
Analytical platforms run queries across terabytes of data.
Spatial & temporal workloads demand multi-dimensional indexing.
And storage hardware itself has evolved, shifting from spinning disks to SSDs and beyond.

👉 In this reality, traditional indexing alone cannot keep up.

This article explores the modern indexing ecosystem—structures and strategies that are no longer “optional,” but fundamental to building scalable, high-performance systems:

Write-Optimized Indexing

Log-Structured Merge (LSM) Trees buffer writes in memory before merging them to disk.
- Core of RocksDB, Cassandra, LevelDB.
- Handles massive insert/update workloads.
Buffer Trees generalize the idea of batching—reducing I/O complexity to near-optimal levels.

Bitmap Indices

Designed for low-cardinality attributes.
Use bit vectors + compression (Roaring, WAH) to allow lightning-fast set operations.
The backbone of data warehouses and OLAP systems.

Spatial & Temporal Indices

R-Trees for spatial queries (GIS, mapping, geometry).
Interval Trees & Hybrids for temporal data (auditing, versioning, time-series).
Enable efficient nearest-neighbor, intersection, and range queries where B+-trees fail.

PostgreSQL’s Index Arsenal

Postgres unifies theory and practice:

B-Tree, Hash → Classic queries.
GiST, SP-GiST → Extensible for unstructured/spatial data.
GIN, BRIN → Full-text search & large sequential datasets.
Advanced features like multicolumn, covering indexes, and index-only scans give developers surgical performance control.

Why this matters

Index design is not an afterthought—it is the foundation of performance engineering. Whether you’re building a real-time system, a warehouse, or a geospatial application, understanding these structures determines if your database scales gracefully or collapses under pressure.

Read the full article in my Notion blog here:

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