This content originally appeared on DEV Community and was authored by realNameHidden
Discover the key difference between HashMap and ConcurrentHashMap in Java with simple examples, use cases, and best practices for writing thread-safe code.
🧩 Introduction
Imagine you’re managing a shared online shopping cart. Multiple users (threads) are adding and removing items at the same time. Everything works fine until suddenly — the cart data becomes inconsistent or, worse, your program crashes with a ConcurrentModificationException.
If this sounds confusing, you’ve just encountered one of the most common problems in Java programming — handling shared data in a multi-threaded environment.
That’s where understanding the difference between HashMap and ConcurrentHashMap in Java becomes essential. Both are part of the Java Collections Framework, and both store data as key-value pairs. But while HashMap is designed for speed in single-threaded programs, ConcurrentHashMap ensures safety and consistency when multiple threads access the same data.
⚙️ Core Concepts
Let’s break down both maps to understand their behavior, structure, and use cases.
1. HashMap — The Fast, Non-Thread-Safe Performer
Think of a HashMap as a fast clerk who manages data efficiently when working alone. It stores elements as key-value pairs and allows null keys and values. However, when multiple threads (clerks) try to update it simultaneously, chaos ensues — leading to data corruption or exceptions.
- Data structure used: Array of buckets + linked lists (or trees after Java 8)
- Thread safety: ❌ Not thread-safe
- Performance: ⚡ Very fast in single-threaded scenarios
- Null values: ✅ Allowed (1 null key, multiple null values)
- Use case: Ideal for single-threaded applications like caching, configuration storage, or lookups.
However, if you try to modify a HashMap from multiple threads without synchronization, you risk losing data integrity.
2. ConcurrentHashMap — The Thread-Safe Multitasker
Now imagine multiple clerks working together in different sections of a store — each responsible for their own area, without interfering with others. That’s exactly how a ConcurrentHashMap works.
It’s designed for concurrent access — allowing multiple threads to read and update the map safely without locking the entire structure.
- Data structure used: Segmented buckets with internal locks (fine-grained locking)
- Thread safety: ✅ Thread-safe and consistent during concurrent operations
- Performance: ⚡ Excellent — better concurrency, minimal locking
-
Null values: ❌ Not allowed (throws
NullPointerException) - Use case: Perfect for multi-threaded environments like web servers, caching systems, and background data processors.
With Java 8 and above, ConcurrentHashMap uses lock striping and non-blocking algorithms to boost performance even under heavy concurrency.
3. Quick Comparison Table
| Feature | HashMap | ConcurrentHashMap |
|---|---|---|
| Thread Safety | Not thread-safe | Thread-safe |
| Performance | Fast in single-threaded apps | Optimized for multi-threaded apps |
| Null Keys/Values | Allows one null key and many null values | Doesn’t allow null keys or values |
| Fail-Fast Behavior | Yes, during iteration | No, uses fail-safe iterators |
| Synchronization Needed | Yes (manually) | No (built-in concurrency control) |
| Use Case | Single-threaded | Multi-threaded |
💻 Code Examples (Java 21)
Example 1: Using HashMap (Single-Threaded Environment)
import java.util.HashMap;
public class HashMapExample {
public static void main(String[] args) {
// Create a HashMap to store employee data
HashMap<Integer, String> employees = new HashMap<>();
// Add key-value pairs
employees.put(101, "Alice");
employees.put(102, "Bob");
employees.put(103, "Charlie");
// Access elements
System.out.println("Employee 102: " + employees.get(102));
// Iterate over entries
employees.forEach((id, name) ->
System.out.println("ID: " + id + ", Name: " + name)
);
// Remove an entry
employees.remove(103);
System.out.println("Updated HashMap: " + employees);
}
}
📝 Explanation:
HashMap works beautifully in a single-threaded context — fast and simple. But if multiple threads modify it simultaneously, the results become unpredictable.
Example 2: Using ConcurrentHashMap (Multi-Threaded Environment)
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
public class ConcurrentHashMapExample {
public static void main(String[] args) {
// Create a thread-safe ConcurrentHashMap
Map<String, Integer> stockPrices = new ConcurrentHashMap<>();
// Thread 1: Adds stock prices
Thread t1 = new Thread(() -> {
stockPrices.put("TCS", 3700);
stockPrices.put("Infosys", 1450);
});
// Thread 2: Updates stock prices
Thread t2 = new Thread(() -> {
stockPrices.put("TCS", 3800);
stockPrices.put("HDFC", 1680);
});
// Start both threads
t1.start();
t2.start();
// Wait for threads to finish
try {
t1.join();
t2.join();
} catch (InterruptedException e) {
e.printStackTrace();
}
// Safely iterate without ConcurrentModificationException
System.out.println("Updated Stock Prices: " + stockPrices);
}
}
📝 Explanation:
ConcurrentHashMap allows multiple threads to read and update data safely — without locking the entire map. It also prevents ConcurrentModificationException, ensuring consistent results even under concurrent access.
✅ Best Practices for Using HashMap and ConcurrentHashMap
- Know Your Environment:
- Use
HashMapfor single-threaded applications. - Use
ConcurrentHashMapfor multi-threaded or parallel processing.
Avoid Null Keys and Values in ConcurrentHashMap:
They are not allowed because null values make it hard to distinguish between “key not found” and “key mapped to null.”Don’t Manually Synchronize ConcurrentHashMap:
It already manages concurrency internally — adding external synchronization can hurt performance.Use Atomic Operations Wisely:
Methods likeputIfAbsent(),computeIfPresent(), andreplace()help avoid race conditions.Iterate Carefully:
Iterators inConcurrentHashMapare fail-safe — meaning they won’t throw exceptions during concurrent modification, but they might not reflect the latest changes immediately.
🏁 Conclusion
The difference between HashMap and ConcurrentHashMap in Java lies mainly in thread safety and performance under concurrency.
- Use HashMap when you’re working in a simple, single-threaded setup — it’s lightweight and fast.
- Use ConcurrentHashMap when multiple threads need to safely share and update data without explicit locks.
By understanding these two, you can build applications that are both efficient and reliable, whether you’re writing a simple script or a high-performance backend system.
This content originally appeared on DEV Community and was authored by realNameHidden
realNameHidden | Sciencx (2025-11-03T14:00:00+00:00) Difference between HashMap and ConcurrentHashMap in Java. Retrieved from https://www.scien.cx/2025/11/03/difference-between-hashmap-and-concurrenthashmap-in-java/
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