Types of MongoDB Indexes

MongoDB offers several index types, each suited to different data shapes and query patterns:

1. Single Field Index
2. Compound Index
3. Multikey Index
4. Geospatial Indexes
5. Text Index
6. Wildcard Index

1. Single Field Index

An index on one field, ascending (1) or descending (-1).

db.students.createIndex({ "roll": 1 })

2. Compound Index

Indexes multiple fields together. MongoDB sorts by the first field, then by the second within each group of the first, and so on — useful when your queries regularly filter or sort by the same combination of fields.

db.collection.createIndex({ field1: 1, field2: 1 })

db.student3.createIndex({ age: 1, name: 1 })

db.student3.find().sort({ age: 1, name: 1 })
// documents are ordered by age first, then by name within the same age

3. Multikey Index

Automatically created when you index a field that holds an array. MongoDB indexes every element of the array individually, so a query can match on any single value inside it.

db.student4.createIndex({ marks: 1 })

db.student4.find({ marks: [40, 70, 90] })

4. Geospatial Indexes

Used to query location-based data (coordinates). MongoDB provides 2d (legacy flat coordinates) and 2dsphere (spherical/Earth-like geometry) indexes.

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

5. Text Index

Enables full-text search over string content in a field.

db.student5.createIndex({ name: "text" })

db.student5.find({ $text: { $search: "gupta" } })

6. Wildcard Index

Indexes an entire subtree of fields under a key, matched with .$** — useful when the shape of your sub-documents is unpredictable (many similar but not-quite-uniform fields).

db.student6.createIndex({ "marks.$**": 1 })

db.student6.find({ "marks.mark1": 60 })
db.student6.find({ "marks.mark2": 60 })
// both queries use the same wildcard index

By default, a wildcard index excludes _id unless you explicitly include it.

Common Errors & Troubleshooting

• Creating a compound index in the wrong field order — a compound index on {a:1, b:1} helps queries filtering on a alone, or a and b together, but does not help a query filtering on b alone — field order matters.
• Expecting a text index to support partial-word matching — $text search matches whole (stemmed) words, not substrings — searching "data" won't match "database" the way a LIKE '%data%'-style pattern would.
• Only one text index allowed per collection — unlike other index types, MongoDB only permits a single text index per collection (though it can span multiple fields).

Key Takeaways

• Compound indexes speed up queries that filter/sort on multiple fields together — field order in the index matters.
• Indexing an array field automatically becomes a multikey index — no special syntax needed.
• Text and geospatial indexes unlock query operators ($text, $near, etc.) that don't work without them.