MongoDB provides a broad range of index types and features with language-specific sort orders to support complex access patterns to your data. Compound indexes are created by combining multiple fields, following the ESR rule for optimal performance. Covered queries return results from an index directly without accessing source documents, and can be identified using the `explain()` method. Indexes on low-cardinality fields should exhibit high cardinality, while unnecessary indexes consume resources and should be eliminated. Wildcard indexes offer flexibility but require careful planning, and text search is useful for matching specific words in a field. Partial indexes reduce performance overhead by only including documents that will be accessed through the index. Multi-key indexes are used for querying arrays, and regular expressions should be carefully chosen to avoid inefficiencies. Index optimizations available in the WiredTiger storage engine can improve performance, and visualization tools like MongoDB Compass and Atlas Data Explorer provide insights into index coverage and usage. Automated index recommendations are available in MongoDB Atlas, providing sample queries and threshold-based slow query detection.