Advanced Indexing

Beyond basic single-field and compound indexes, MongoDB offers specialized index types for text search, geographic queries, and complex indexing strategies that balance read speed against write cost.

1. Text Indexes

Text indexes enable full-text search across string fields, with support for stemming and relevance scoring.

db.articles.createIndex({ title: "text", content: "text" })

// Search for documents containing "mongodb" or "database"
db.articles.find({ $text: { $search: "mongodb database" } })

// Sort by relevance score
db.articles.find(
  { $text: { $search: "aggregation pipeline" } },
  { score: { $meta: "textScore" } }
).sort({ score: { $meta: "textScore" } })

2. Geospatial Indexes

Geospatial indexes support location-based queries — finding nearby points, points within a shape, or intersecting geometries.

// GeoJSON point format
db.stores.insertOne({
  name: "Downtown Cafe",
  location: { type: "Point", coordinates: [77.5946, 12.9716] }  // [longitude, latitude]
})

db.stores.createIndex({ location: "2dsphere" })

// Find stores within 5km of a point
db.stores.find({
  location: {
    $near: {
      $geometry: { type: "Point", coordinates: [77.60, 12.97] },
      $maxDistance: 5000
    }
  }
})

3. Wildcard Indexes

Wildcard indexes index all fields (or a subset) dynamically — useful for collections with unpredictable, user-defined schemas.

db.userSettings.createIndex({ "preferences.$**": 1 })

4. TTL (Time-To-Live) Indexes

TTL indexes automatically delete documents after a specified number of seconds — perfect for session data or temporary logs.

db.sessions.createIndex(
  { createdAt: 1 },
  { expireAfterSeconds: 3600 }  // Auto-delete after 1 hour
)

5. Indexing Strategy Considerations

6. Advanced Indexing Checklist

• ✅ Create and query text indexes
• ✅ Use 2dsphere indexes for geospatial queries
• ✅ Apply TTL indexes for auto-expiring data
• ✅ Periodically audit index usage with $indexStats