C++ Multimap: A Comprehensive Guide

Data management and retrieval are critical components within the realm of C++ programming, and they have the potential to significantly influence the efficacy and efficiency of your applications. Multimap in C++ is an adaptable instrument that can assist you in accomplishing this. Exhaustive coverage of the functionality, applications, and much more of the C++ multimap will be provided in this article.

What is a Multimap?

As an introductory step, it is imperative that we define a multimap within the framework of C++. A multimap is an adaptable data structure that, similar to a standard map, permits the storage of key-value pairs. Nevertheless, it diverges in a pivotal way: it has the capability to store multiple values for a given variable. This characteristic renders it highly practical in specific situations that require the association of multiple values with a solitary key.

What is a C++ Multimap?

A ‘multimap’ is a category of associative container that is made available in C++ via the Standard Template Library1. Like a standard ‘map’, it permits the storage of key-value pairs; however, a ‘multimap’ allows for the inclusion of multiple entries with the same key. 

The following are essential attributes and functionalities of a C++ “multimap”:

Associative Container: One notable characteristic of this container is its associative nature, which ensures that elements are stored in a key-sorted fashion. This facilitates retrieval and lookup operations that are optimized for the keys.

Ordered: In an ascending order, the elements within a ‘multimap’ are arranged according to their keys. This ordering facilitates the execution of operations such as deletion, insertion, and searching with greater efficiency.

In contrast to a ‘map’ which mandates the use of unique keys, a ‘multimap’ permits the inclusion of multiple entries that share the same key. When you need to associate multiple values with a single key, this is useful.

Executed as a Red-Black Tree: From an internal perspective, a ‘multimap’ is conventionally implemented as a self-balancing binary search tree known as a Red-Black Tree. This design feature guarantees that operations such as insertion and deletion are executed with optimal efficiency, all the while preserving the sorted order.

The following is an instance of utilizing a ‘multimap’ in C++:

#include <iostream>
#include <map>

int main() {
    std::multimap<int, std::string> myMultimap;

    // Inserting values with duplicate keys
    myMultimap.insert(std::make_pair(1, "Apple"));
    myMultimap.insert(std::make_pair(2, "Banana"));
    myMultimap.insert(std::make_pair(1, "Apricot"));
    myMultimap.insert(std::make_pair(3, "Cherry"));

    // Iterating through the multimap
    for (const auto& pair : myMultimap) {
        std::cout << pair.first << ": " << pair.second << std::endl;

    return 0;

The’multimap’ function permits the inclusion of multiple values for a given key (e.g., key 1 contains both “Apple” and “Apricot”). As you iterate over the ‘multimap’, each key-value pair will be displayed in key-value order.

The C++ container’multimap’ is a valuable tool for managing a sorted collection of key-value pairs, including those that might contain duplicate keys.

Why Use a Multimap?

Programming with a multimap is advantageous due to its numerous benefits and specific use cases, which render it a valuable option:

Handling Duplicate Keys: Multimaps enable the assignment of multiple values to a single key. When dealing with or maintaining records that may contain duplicate keys, a multimap is an ideal solution. In a database, for instance, there may be numerous entries that share the same identity or identifier.

Grouping Data: The utilization of multimaps is highly effective in the process of categorizing data that is related. A common key can be employed to link together diverse parts of information. This feature proves to be advantageous in situations requiring hierarchical data organization or items possessing multiple attributes.

Counting Occurrences: A multimap can be a highly efficient option when the objective is to determine the number of occurrences of a particular item, event, or value. The item is denoted by the key, while the counts are stored in the values, facilitating the retrieval and modification of counts.

Ordered Storage: In the case of ordered storage, multimaps preserve the arrangement of elements according to their keys. This functionality may streamline operations such as locating a range of values within a specified key range or retrieving items in a predetermined order. This is particularly useful in situations requiring categorized data, such as alphabetical catalogs.

Efficient Data Retrieval: Multimaps offer efficient data retrieval in situations where frequent key-based searches are required, due to their typical implementation as self-balancing binary search trees. This guarantees the time complexity of key-based operations to be logarithmic.

Simplified Data Management: Particularly when coping with many-to-many or one-to-many relationships, multimaps can facilitate data management. Complex logic or the implementation of custom data structures is not required to manage multiple values per key.

Natural for Relationships: Multimaps are an inherent and logical selection when it comes to representing relationships within datasets. For instance, a multimap can be utilized in a social networking application to link individuals with their peers or followers.

STL Integration: Multimaps are a component of the Standard Template Library (STL) in programming languages such as C++. This indicates that they are well-tested, include a vast array of pre-implemented features, and can be combined effortlessly with other STL containers and algorithms.

Versatility: Multimaps are applicable to a wide range of applications, including algorithmic problem-solving, database implementation, and hierarchical data management.

Code Complexity Reduction: Implementing a multimap can streamline your code. When dealing with situations that require the creation of custom data structures or the management of complex logic to accommodate multiple values per key, a multimap offers a direct and effective alternative.

A multimap should be utilized when working with data containing duplicate variables or when efficiently organizing related data. Multimaps are highly suitable for the purpose of organizing data in a categorized fashion and streamlining the management of one-to-many relationships; thus, they prove to be a valuable instrument in a multitude of programming contexts.

How to Implement a Multimap

Now that we understand the significance of a multimap, let’s explore how to implement one in C++. The standard template library (STL) offers a robust implementation of multimaps, and using them is straightforward.

Step 1: Include the Necessary Headers

To start using multimaps, you need to include the appropriate headers in your C++ code:

#include <iostream>
#include <map>

Step 2: Declare and Use a Multimap

Next, you can declare a multimap and begin using it in your code:

std::multimap<KeyType, ValueType> myMultimap;
myMultimap.insert({key, value});

Common Operations with Multimaps

Multimaps support various operations that facilitate efficient data management. Here are some of the most common operations you can perform:

Inserting Key-Value Pairs

myMultimap.insert({key, value});

Accessing Values by Key

auto range = myMultimap.equal_range(key);
for (auto it = range.first; it != range.second; ++it) {
    // Access and work with the values

Removing Entries


Checking for Existence

if (myMultimap.find(key) != myMultimap.end()) {
    // Key exists

Advantages of Using Multimaps

The utilization of multimaps in programming presents numerous benefits across diverse scenarios:

Support for Duplicate Keys: The ability to utilize redundant variables is one of the principal benefits associated with the implementation of multimaps. When you need to associate multiple values with the same key, this is advantageous. To manage such circumstances in the absence of this feature, a more intricate data structure or collection would be required.

Efficient Grouping: A beneficial feature of multimaps is their efficiency in organizing data that is related. Multiple values can be associated with a common identifier, which simplifies the management and processing of data with a many-to-many or one-to-many relationship.

Counting Occurrences: Multimaps are useful when counting the occurrences of particular products or events. The key can be utilized to denote the item, while the values can be stored to indicate the number of occurrences. This is especially beneficial for applications such as frequency analysis.

Ordered Data: In the case of ordered data, multimaps preserve the arrangement of elements according to their keys. By ensuring that the elements are sorted, this process facilitates the efficient retrieval of a range of values within a specified key range or the identification and manipulation of specific key-value pairs.

Data Storage Simplified: Multimaps can streamline the process of storing and retrieving code when working with data that possesses hierarchical or categorized attributes. This may result in code that is more legible and concise.

Flexibility and Convenience: Multimaps offer a streamlined approach to managing collections comprising keys and numerous correlated values. For managing multiple values per key, neither implementation of custom data structures nor management of complex logic is required.

STL Integration: Multimaps, which are extensively used, efficient, and well-tested, is a component of the Standard Template Library (STL) in programming languages such as C++. This standardization guarantees compatibility and consistency with alternative STL containers and algorithms.

Efficient Operations: Self-balancing binary search trees, such as Red-Black Trees, are commonly used to implement multimaps. These trees offer efficient operations including insertion, deletion, and searching, even when dealing with large data sets.

Versatile Use Cases: Multimaps find applications in a wide range of use cases, including but not limited to database implementation, data structure construction for natural language processing, and algorithmic problem-solving involving efficient data organization.

Code Complexity Reduction: The implementation of multimaps can effectively mitigate code complexity, particularly in situations where intricate data structures and bespoke logic are required to process multiple values associated with a single key.

In essence, multimaps are advantageous data structures that offer adaptability and effectiveness when multiple values must be associated with a single key and must be maintained in a sorted state. Their broad applicability to various situations renders them an adaptable instrument for data management and processing in programming.


In summary, the C++ multimap is a robust instrument that has the capability to optimize data retrieval and organization within your applications. Its exceptional capability to link multiple values to a solitary key renders it indispensable in a multitude of situations. Proficiency in effectively utilizing and capitalizing on multimaps can significantly enhance the efficiency of C++ programs.

Frequently Asked Questions (FAQs)

Can a multimap store multiple values for the same key?

Yes, that’s one of the defining features of a multimap. It can associate multiple values with the same key.

Is there a limit to the number of values a multimap can store for a single key?

No, there’s no predefined limit. Multimaps can store as many values as needed for a single key.

Are multimaps part of the C++ Standard Library?

Yes, multimaps are part of the C++ Standard Library and can be used in any C++ program.

What’s the difference between a map and a multimap in C++?

The key difference is that a map can only store one value for each key, while a multimap can store multiple values for the same key.

When should I use a multimap in my C++ programs?

You should consider using a multimap when you need to associate multiple values with a single key in your data structures. It’s especially useful in situations where flexibility and efficient retrieval are essential.

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