Difference between HashMap and ConcurrentHashMap in Java

Discover the key difference between HashMap and ConcurrentHashMap in Java with simple examples, use cases, and best practices for writing thread-safe code.

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🧩 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.

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⚙️ 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.

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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.

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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

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💻 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.

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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.

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✅ Best Practices for Using HashMap and ConcurrentHashMap

1. Know Your Environment:

• Use HashMap for single-threaded applications.
• Use ConcurrentHashMap for multi-threaded or parallel processing.

1. 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.”

2. Don’t Manually Synchronize ConcurrentHashMap:
   It already manages concurrency internally — adding external synchronization can hurt performance.

3. Use Atomic Operations Wisely:
   Methods like putIfAbsent(), computeIfPresent(), and replace() help avoid race conditions.

4. Iterate Carefully:
   Iterators in ConcurrentHashMap are fail-safe — meaning they won’t throw exceptions during concurrent modification, but they might not reflect the latest changes immediately.

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🏁 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.

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