When to use LinkedList over ArrayList in Java?

Choosing the right data structure in Java can profoundly impact your application’s performance and maintainability. Both ArrayList and LinkedList implement the List interface, but they differ in how they store elements and perform operations. While ArrayList is often the default go-to choice, there are specific scenarios where LinkedList might be more appropriate.

In this guide, we’ll break down the differences between ArrayList and LinkedList, focusing on when and why you’d choose LinkedList over ArrayList. We’ll explore performance characteristics, memory considerations, and use cases. By the end, you’ll have the knowledge you need to confidently pick the right data structure for your specific scenario.

Data Structure Differences
When ArrayList Shines
When to Use LinkedList
Practical Examples
Performance Benchmarks and Considerations
Recommended Courses to Enhance Your Java Skills
Additional Resources for Interview Preparation
Conclusion

1. Data Structure Differences

ArrayList:

Internally Backed by Array:
ArrayList uses a dynamically resizing array. Adding elements at the end is typically O(1), but inserting or removing from the middle requires shifting elements, resulting in O(n) complexity.
Random Access:
ArrayList provides fast random access (O(1)) to elements by index.

LinkedList:

Doubly Linked Nodes:
LinkedList stores elements in a chain of nodes, each holding references to the previous and next elements. Insertions and deletions at the head or tail are O(1).
No Direct Random Access:
Accessing an element by index requires traversing from one node to another, resulting in O(n) complexity.

2. When `ArrayList` Shines

ArrayList is often the default choice due to its simplicity and performance characteristics:

Fast Random Access:
Need quick lookups by index? ArrayList is ideal.
Frequent Iteration:
ArrayList supports efficient iteration, as elements are stored contiguously in memory.
Append-Heavy Operations:
Adding elements to the end of an ArrayList is generally O(1), making it suitable for use cases like dynamic arrays or stacks.

3. When to Use `LinkedList`

While LinkedList is not as commonly chosen as ArrayList, it excels in specific scenarios:

Frequent Insertions and Deletions in the Middle:
If you need to frequently insert or remove elements at arbitrary positions (especially near the head or tail), LinkedList shines. These operations can often be O(1) once you have a node reference.
Implementing Deque or Queue-like Structures:
LinkedList implements the Deque interface, making operations like offerFirst(), offerLast(), pollFirst(), and pollLast() efficient. It naturally models queues, double-ended queues, and stacks.
Iterator-Based Removal:
If you use an iterator to locate an element, removing it via the iterator on a LinkedList is O(1). With ArrayList, removal still involves shifting elements.
Stable Insertions Under Memory Re-allocation Pressures:
ArrayList can occasionally reallocate and copy the underlying array when it grows. If you suspect large and unpredictable growth, LinkedList may spare you the cost of reallocations (though at the expense of less cache-friendly access patterns).

In short: Opt for LinkedList if you need efficient insertion or removal in the middle of the list, or if you’re modeling a queue-like structure with frequent additions and removals from ends.

4. Practical Examples

Use Case: Transaction Processing Queue

If you’re building a system that processes incoming transactions in a FIFO order, a queue-like structure is ideal. Using a LinkedList as a queue makes poll() and offer() at the ends O(1), providing consistent performance for enqueue and dequeue operations.

Use Case: Undo/Redo Stacks

Implementing an undo/redo feature might require adding or removing from the head of a list frequently. LinkedList can handle these operations seamlessly.

Use Case: Frequent Intermediate Insertions

Suppose you are maintaining a list of subscribers and frequently insert new subscribers in sorted order. With LinkedList, if you have a reference to the correct position (e.g., found via an iterator), insertion is O(1). In an ArrayList, insertion requires shifting subsequent elements.

5. Performance Benchmarks and Considerations

Memory Usage:
LinkedList incurs more overhead due to node objects and references. ArrayList stores elements contiguously and can be more memory-efficient and cache-friendly.

Traversal Costs:
While LinkedList excels at insertions and deletions at known positions, random access is costly. If you often need to get elements by index (e.g., list.get(i)), ArrayList will outperform LinkedList dramatically.

Practical Advice:
Measure your application’s performance. Modern JVMs and hardware optimizations sometimes make the differences less pronounced. Use profilers and benchmarks like JMH to confirm which list is genuinely better for your specific use case.

6. Recommended Courses to Enhance Your Java Skills

Choosing between LinkedList and ArrayList is just one element of writing high-quality Java code. To excel as a Java developer, you need a solid foundation in design principles, system design, and coding interviews.

Recommended Courses from DesignGurus.io:

Grokking SOLID Design Principles
Learn how to structure your classes and methods following SOLID principles, making it easier to integrate the right data structures into maintainable codebases.
Grokking Design Patterns for Engineers and Managers
Understand common patterns that help you choose and adapt data structures effectively.

For expanding into system design and interview patterns:

7. Additional Resources for Interview Preparation

Blogs by DesignGurus.io:

YouTube Channel:
Check out the DesignGurus YouTube Channel for insights on system design, coding patterns, and preparation tips.

Mock Interviews and Services:

Get personalized feedback from ex-FAANG engineers to refine your interviewing strategy.

8. Conclusion

While ArrayList is often the default choice due to its simplicity and efficient random access, LinkedList shines when you need frequent insertions and deletions, particularly at the ends or when using iterator-based operations. By carefully analyzing your use case—whether you’re building queues, managing frequently changing lists, or modeling data structures that rely on efficient insertions—you can determine if LinkedList is the better fit.

Combining this understanding with strong design principles, coding patterns, and system design insights will help you build robust, efficient, and scalable Java applications—and ace those all-important technical interviews.

Choose the right tool for the job. Leverage LinkedList for insertion-heavy workloads and ArrayList for random access.