Select data structures based on specific access patterns and performance requirements. When both fast lookup and predictable iteration order are needed, specialized structures like IndexMap offer benefits over standard HashMap: ```rust // When order matters and lookups are frequent: use indexmap::IndexMap; // Fast lookups + preserved insertion order let cache: IndexMap = IndexMap::new(); // Regular HashMap when only lookup speed matters let simple_lookup: HashMap = HashMap::new(); ``` For serialization, separate concerns from runtime efficiency - use simple Vector structures for serialization, then transform into Maps for runtime lookups. This avoids serializing complex key structures while maintaining fast access patterns: ```rust // For serialization - simple Vec let serializable_data: Vec = items.into_iter().collect(); // For runtime - efficient HashMap let lookup_map: HashMap = serializable_data.into_iter() .map(|item| (item.id, item)) .collect(); ``` When implementing caches, consider using reference-based APIs like `entry_ref` from hashbrown to avoid unnecessary cloning: ```rust use hashbrown::HashMap; // Avoids cloning the key for lookup map.entry_ref(key_reference).or_insert_with(|| create_value()); ``` Document your data structure choices to explain performance tradeoffs, especially when choosing specialized structures over standard library alternatives.