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C#, C++ and Java Containers

The following documentation is extracted from several websites which discuss C#(C-sharp), C++ and Java Containers and their performance.

Links and names of the authors are provided above each document.

cs C#/NET
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C# Containers
From James Michael Hare June 16, 2011

C#/.NET Fundamentals: Choosing the Right Collection Class

The .NET Base Class Library (BCL) has a wide array of collection classes at your disposal which make it easy to manage collections of objects. While it's great to have so many classes available, it can be daunting to choose the right collection to use for any given situation. As hard as it may be, choosing the right collection can be absolutely key to the performance and maintainability of your application!

This post will look at breaking down any confusion between each collection and the situations in which they excel. We will be spending most of our time looking at the System.Collections.Generic namespace, which is the recommended set of collections.

The Generic Collections: System.Collections.Generic namespace

The generic collections were introduced in .NET 2.0 in the System.Collections.Generic namespace. This is the main body of collections you should tend to focus on first, as they will tend to suit 99% of your needs right up front.

It is important to note that the generic collections are unsynchronized. This decision was made for performance reasons because depending on how you are using the collections its completely possible that synchronization may not be required or may be needed on a higher level than simple method-level synchronization. Furthermore, concurrent read access (all writes done at beginning and never again) is always safe, but for concurrent mixed access you should either synchronize the collection or use one of the concurrent collections.

So let's look at each of the collections in turn and its various pros and cons, at the end we'll summarize with a table to help make it easier to compare and contrast the different collections.

The Associative Collection Classes

Associative collections store a value in the collection by providing a key that is used to add/remove/lookup the item. Hence, the container associates the value with the key. These collections are most useful when you need to lookup/manipulate a collection using a key value. For example, if you wanted to look up an order in a collection of orders by an order id, you might have an associative collection where they key is the order id and the value is the order.

The Dictionary<TKey,TVale> is probably the most used associative container class. The Dictionary<TKey,TValue> is the fastest class for associative lookups/inserts/deletes because it uses a hash table under the covers. Because the keys are hashed, the key type should correctly implement GetHashCode() and Equals() appropriately or you should provide an external IEqualityComparer to the dictionary on construction. The insert/delete/lookup time of items in the dictionary is amortized constant time - O(1) - which means no matter how big the dictionary gets, the time it takes to find something remains relatively constant. This is highly desirable for high-speed lookups. The only downside is that the dictionary, by nature of using a hash table, is unordered, so you cannot easily traverse the items in a Dictionary in order.

The SortedDictionary<TKey,TValue> is similar to the Dictionary<TKey,TValue> in usage but very different in implementation. The SortedDictionary<TKey,TValye> uses a binary tree under the covers to maintain the items in order by the key. As a consequence of sorting, the type used for the key must correctly implement IComparable<TKey> so that the keys can be correctly sorted. The sorted dictionary trades a little bit of lookup time for the ability to maintain the items in order, thus insert/delete/lookup times in a sorted dictionary are logarithmic - O(log n). Generally speaking, with logarithmic time, you can double the size of the collection and it only has to perform one extra comparison to find the item. Use the SortedDictionary<TKey,TValue> when you want fast lookups but also want to be able to maintain the collection in order by the key.

The SortedList<TKey,TValue> is the other sorted associative container class in the generic containers. Once again SortedList<TKey,TValue>, like SortedDictionary<TKey,TValue>, uses a key to sort key-value pairs. Unlike SortedDictionary, however, items in a SortedList are stored as sorted array of items. This means that insertions and deletions are linear - O(n) - because deleting or adding an item may involve shifting all items up or down in the list. Lookup time, however is O(log n) because the SortedList can use a binary search to find any item in the list by its key. So why would you ever want to do this? Well, the answer is that if you are going to load the SortedList up-front, the insertions will be slower, but because array indexing is faster than following object links, lookups are marginally faster than a SortedDictionary. Once again I'd use this in situations where you want fast lookups and want to maintain the collection in order by the key, and where insertions and deletions are rare.

The Non-Associative Containers

The other container classes are non-associative. They don't use keys to manipulate the collection but rely on the object itself being stored or some other means (such as index) to manipulate the collection.

The List<T> is a basic contiguous storage container. Some people may call this a vector or dynamic array. Essentially it is an array of items that grow once its current capacity is exceeded. Because the items are stored contiguously as an array, you can access items in the List<T> by index very quickly. However inserting and removing in the beginning or middle of the List<T> are very costly because you must shift all the items up or down as you delete or insert respectively. However, adding and removing at the end of a List<T> is an amortized constant operation - O(1). Typically List<T> is the standard go-to collection when you don't have any other constraints, and typically we favor a List<T> even over arrays unless we are sure the size will remain absolutely fixed.

The LinkedList<T> is a basic implementation of a doubly-linked list. This means that you can add or remove items in the middle of a linked list very quickly (because there's no items to move up or down in contiguous memory), but you also lose the ability to index items by position quickly. Most of the time we tend to favor List<T> over LinkedList<T> unless you are doing a lot of adding and removing from the collection, in which case a LinkedList<T> may make more sense.

The HashSet<T> is an unordered collection of unique items. This means that the collection cannot have duplicates and no order is maintained. Logically, this is very similar to having a Dictionary<TKey,TValue> where the TKey and TValue both refer to the same object. This collection is very useful for maintaining a collection of items you wish to check membership against. For example, if you receive an order for a given vendor code, you may want to check to make sure the vendor code belongs to the set of vendor codes you handle. In these cases a HashSet<T> is useful for super-quick lookups where order is not important. Once again, like in Dictionary, the type T should have a valid implementation of GetHashCode() and Equals(), or you should provide an appropriate IEqualityComparer<T> to the HashSet<T> on construction.

The SortedSet<T> is to HashSet<T> what the SortedDictionary<TKey,TValue> is to Dictionary<TKey,TValue>. That is, the SortedSet<T> is a binary tree where the key and value are the same object. This once again means that adding/removing/lookups are logarithmic - O(log n) - but you gain the ability to iterate over the items in order. For this collection to be effective, type T must implement IComparable<T> or you need to supply an external IComparer<T>.

Finally, the Stack<T> and Queue<T> are two very specific collections that allow you to handle a sequential collection of objects in very specific ways. The Stack<T> is a last-in-first-out (LIFO) container where items are added and removed from the top of the stack. Typically this is useful in situations where you want to stack actions and then be able to undo those actions in reverse order as needed. The Queue<T> on the other hand is a first-in-first-out container which adds items at the end of the queue and removes items from the front. This is useful for situations where you need to process items in the order in which they came, such as a print spooler or waiting lines.

So that's the basic collections. Let's summarize what we've learned in a quick reference table.

Collection Ordering Contiguous Storage? Direct Access? Lookup Efficiency Manipulate Efficiency Notes
Dictionary Unordered Yes Key Key:O(1) O(1) Best for high performance lookups.
SortedDictionary Sorted No Via Key Key:
O(log n)
O(log n) Compromise of Dictionary speed and ordering, uses binary search tree.
SortedList Sorted Yes Via Key Key:
O(log n)
O(n) Very similar to SortedDictionary, except tree is implemented in an array, so has faster lookup on preloaded data, but slower loads.
List User has precise control over element ordering Yes Via Index Index: O(1) Value: O(n) O(n) Best for smaller lists where direct access required and no sorting.
LinkedList User has precise control over element ordering No No Value: O(n) O(1) Best for lists where inserting/deleting in middle is common and no direct access required.
HashSet Unordered Yes Via Key Key: O(1) O(1) Unique unordered collection, like a Dictionary except key and value are same object.
SortedSet Sorted No Via Key Key: O(log n) O(log n) Unique sorted collection, like SortedDictionary except key and value are same object.
Stack LIFO Yes Only Top Top: O(1) O(1)* Essentially same as List<T> except only process as LIFO
Queue FIFO Yes Only Front O(1) O(1) same as List<T> except only process as FIFO
ArrayList User has precise control over element ordering Yes Via Index Index: O(1) Value: O(n) O(n) Best for smaller lists where direct access required and no sorting. Stores objects of any type.


The Original Collections: System.Collections namespace

The original collection classes are largely considered deprecated by developers and by Microsoft itself. In fact they indicate that for the most part you should always favor the generic or concurrent collections, and only use the original collections when you are dealing with legacy .NET code.

Because these collections are out of vogue, let's just briefly mention the original collection and their generic equivalents:

In general, the older collections are non-type-safe and in some cases less performant than their generic counterparts. Once again, the only reason you should fall back on these older collections is for backward compatibility with legacy code and libraries only.

The Concurrent Collections: System.Collections.Concurrent namespace

The concurrent collections are new as of .NET 4.0 and are included in the System.Collections.Concurrent namespace. These collections are optimized for use in situations where multi-threaded read and write access of a collection is desired.

The concurrent queue, stack, and dictionary work much as you'd expect. The bag and blocking collection are more unique. Below is the summary of each with a link to a blog post I did on each of them.


The .NET BCL has lots of collections built in to help you store and manipulate collections of data. Understanding how these collections work and knowing in which situations each container is best is one of the key skills necessary to build more performant code. Choosing the wrong collection for the job can make your code much slower or even harder to maintain if you choose one that doesn't perform as well or otherwise doesn't exactly fit the situation.

Remember to avoid the original collections and stick with the generic collections.  If you need concurrent access, you can use the generic collections if the data is read-only, or consider the concurrent collections for mixed-access if you are running on .NET 4.0 or higher.

.Net Version when Collections are Available

2.0 3.0 3.5 4.0 4.5

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C++ Containers

C++ STL Container Templates

Pete Isensee


Container Stores Overhead [ ] Iterators Insert Erase Find Sort
list T 8 n/a Bidirect'l C C N N log N
deque T 12 C Random C at begin or end; else N/2 C at begin or end; else N N N log N
vector T 0 C Random C at end; else N C at end; else N N N log N
set T, Key 12 n/a Bidirect'l log N log N log N C
multiset T, Key 12 n/a Bidirect'l log N d log (N+d) log N C
map Pair, Key 16 log N Bidirect'l log N log N log N C
multimap Pair, Key 16 n/a Bidirect'l log N d log (N+d) log N C
stack T n/a n/a n/a C C n/a n/a
queue T n/a n/a n/a C C n/a n/a
priority_ queue T n/a n/a n/a log N log N n/a n/a
slist T 4 n/a Forward C C N N log N

John Ahlgren October 13, 2013


Container Insertion Access Erase Find Persistent Iterators
vector / string Back: O(1) or O(n)
Other: O(n)
O(1) Back: O(1)
Other: O(n)
Sorted: O(log n)
Other: O(n)
deque Back/Front: O(1)
Other: O(n)
O(1) Back: O(1)
Other: O(n)
Sorted: O(log n)
Other: O(n)
Pointers only
list / forward_list Back/Front: O(1)
With iterator: O(1)
Index: O(n)
Back/Front: O(1)
With iterator: O(1)
Index: O(n)
Back/Front: O(1)
With iterator: O(1)
Index: O(n)
O(n) Yes
set / map O(log n) - O(log n) O(log n) Yes
unordered_set / unordered_map O(1) or O(n) O(1) or O(n) O(1) or O(n) O(1) or O(n) Pointers only
priority_queue O(log n) O(1) O(log n) - -

Collection Ordering Contiguous Storage? Direct Access? Lookup Efficiency Manipulate Efficiency Notes
array Fixed-size linear sequence. Yes Via Index Index: O(1) Value: O(n) O(n) Adds iterators and STL interface to c/c++ array structures.
vector User controls order Yes Via Index Index: O(1) Value: O(n) O(n) Best for smaller lists where direct access required and no sorting.
deque User controls order No Via Index O(1) O(n) same as vector<T> can use as stack or queue
forward_list Singly-linked lists No Forward iterator Index: O(1) Value: O(n) O(n) Less overhead than List
list Double linked list. No Bidirectional Iterator Index: O(1) Value: O(n) O(n) More overhead than forward_list, bidirectional access
stack LIFO No if deque Only back (top) Top: O(1) O(1)* Essentially same as deque<T> except only process as LIFO
queue FIFO No if deque Only Front O(1) O(1)* Essentially same as deque<T> except only process as FIFO
priority_queue Ordered Yes if vector Only back (top) O(1) O(log n) Priority ordered vector
set Ordered No? Via Key O(log n) O(log n) Unique ordered collection of keys
multiset Ordered No? Via Key O(log n + d) O(log n + d) Ordered collection of keys
map Ordered No? Via Key Key:O(log n) O(log n) Unique keys, high performance lookups.
multimap Ordered No? Via Key O(log n + d) O(log n + d) Duplicate keys, high performance lookups.
unordered_set Unordered No? Via Key Key: O(1) O(1) Faster then set (hashSet)
unordered_multiset Unordered No? Via Key O(1 + d) O(1 + d) Faster than multiset
unordered_map Unordered No? Key O(n) O(n) Faster than map (hashMap)
unordered_multimap Unordered No? Key O(n + d) O(n + d) Faster then multimap

[ Top ]

Java Containers

Java Performance


Java JDK 1.6 Util package

Java Container Templates

Hash Table Resizable Array Balanced Tree Linked List Hash Table + Linked List
Interfaces Set HashSet   TreeSet   LinkedHashSet
List   ArrayList   LinkedList  
Deque   ArrayDeque   LinkedList  
Map HashMap   TreeMap   LinkedHashMap




The core collection interfaces encapsulate different types of collections, which are shown in the figure below. These interfaces allow collections to be manipulated independently of the details of their representation. Core collection interfaces are the foundation of the Java Collections Framework. As you can see in

Note that all the core collection interfaces are generic. For example, this is the declaration of the Collection interface.

public interface Collection<E>...

The <E> syntax tells you that the interface is generic. When you declare a Collection instance you can and should specify the type of object contained in the collection. Specifying the type allows the compiler to verify (at compile-time) that the type of object you put into the collection is correct, thus reducing errors at runtime. For information on generic types, see the

When you understand how to use these interfaces, you will know most of what there is to know about the Java Collections Framework. This chapter discusses general guidelines for effective use of the interfaces, including when to use which interface. You'll also learn programming idioms for each interface to help you get the most out of it.

To keep the number of core collection interfaces manageable, the Java platform doesn't provide separate interfaces for each variant of each collection type. (Such variants might include immutable, fixed-size, and append-only.) Instead, the modification operations in each interface are designated optional - a given implementation may elect not to support all operations. If an unsupported operation is invoked, a collection throws an UnsupportedOperationException. Implementations are responsible for documenting which of the optional operations they support. All of the Java platform's general-purpose implementations support all of the optional operations.

The following list describes the core collection interfaces:

The last two core collection interfaces are merely sorted versions of Set and Map:

Java-Latte Learn with a sip of Latte, September 24, 2013 by pardeep k



Key Interfaces and Classesof Collection Framework

Collection Set SortedSet
List Map SortedMap
Queue NavigableSet NavigableMap

Key Classes of the Collections Framework

Maps Sets Lists Queues Utilities
HashMap HashSet ArrayList PriorityQueue Collections
HashTable LinkedHashSet Vector   Arrays
TreeMap TreeSet LinkedList    

"Concise presentations of java programming practices, tasks, and conventions, amply illustrated with syntax highlighted code examples." http://www.javapractices.com/topic/TopicAction.do?Id=65

Here's a guide for selecting the proper implementation of a Set, List, or Map. It was compiled for Java 1.4. Many additions have been made to the Collections Framework since then (notably the Queue and Deque interfaces, and various items in java.util.concurrent). These later additions have been omitted here, since this briefer summary should suffice for most cases.

The best general purpose or 'primary' implementations are likely ArrayList, LinkedHashMap, and LinkedHashSet. Their overall performance is better, and you should use them unless you need a special feature provided by another implementation. That special feature is usually ordering or sorting.

For convenience, "ordering" will here refer to the order of items returned by an Iterator, and "sorting" will here refer to sorting items according to Comparable or Comparator.

Interface HasDuplicates? Implementations Historical
Set no HashSet ... LinkedHashSet ... TreeSet
List yes ... ArrayList ... LinkedList
Vector, Stack
Map no duplicate keys  HashMap ... LinkedHashMap ... TreeMap Hashtable, Properties

Principal features of non-primary implementations:

Iteration order for above implementations: For LinkedHashSet and LinkedHashMap, the re-insertion of an item does not affect insertion order.

For LinkedHashMap, 'access order' is from the least recent access to the most recent access. In this context, only calls to get, put, and putAll constitute an access, and only calls to these methods affect access order.

While being used in a Map or Set, these items must not change state (hence, it's recommended that these items be immutable objects):

Sorting requires either that: To retain the order of a ResultSet as specified in an ORDER BY clause, insert the records into a List or a LinkedHashMap.