SQL indexes are critical for optimizing query performance. Understanding different index types helps you choose the right one for your use case. Here's a breakdown:

1. B-Tree Index 📂

The most common index type, ideal for range queries and order-by operations.

  • Pros: Efficient for equality and inequality searches
  • Cons: Slower for high-cardinality data
B_Tree

2. Hash Index 🔍

Optimized for exact match queries.

  • Pros: Fast lookup times
  • Cons: Poor for range searches
Hash_Index

3. R-Tree Index 🗺️

Designed for spatial data (e.g., geometry, geolocation).

  • Pros: Efficient for multidimensional data
  • Cons: Complex to implement
R_Tree

4. Full-Text Index 📖

Specialized for text-based searches (e.g., LIKE with wildcards).

  • Pros: Supports natural language queries
  • Cons: Requires significant storage
Full_Text_Index

5. Bitmap Index 🧩

Efficient for low-cardinality columns (e.g., status flags).

  • Pros: Excellent for filtering and joins
  • Cons: Less effective for large datasets
Bitmap_Index

For deeper insights into query optimization, check our tutorial on SQL Query Optimization. 📚