ConcurrentHashMap vs synchronizedMap: Java Thread Safety Guide

ConcurrentHashMap and Collections.synchronizedMap are two primary approaches to thread-safe Map implementations in Java, with significant differences in their locking mechanisms, performance characteristics, and scalability under concurrent access. ConcurrentHashMap uses lock striping and segment-level locking to achieve better performance in high-concurrency scenarios, while Collections.synchronizedMap employs a single lock approach that can become a bottleneck under heavy concurrent load. Understanding these differences is crucial for selecting the right implementation based on your specific concurrency requirements and performance needs.

Contents

• Introduction to Thread-Safe Maps in Java
• ConcurrentHashMap: Implementation and Performance Characteristics
• Collections.synchronizedMap: Implementation and Performance Characteristics
• Key Differences and When to Use Each Implementation
• Performance Comparison and Best Practices
• Sources
• Conclusion

Introduction to Thread-Safe Maps in Java

When building multi-threaded Java applications, ensuring thread-safe collection access is crucial to prevent data corruption and inconsistent states. The standard HashMap is not thread-safe, and concurrent modifications can lead to race conditions, infinite loops, or other unpredictable behavior. Java provides two primary thread-safe Map implementations: ConcurrentHashMap and Collections.synchronizedMap. While both achieve thread safety, they do so through fundamentally different approaches with significant performance implications.

Thread safety in Java collections becomes critical when multiple threads need to read and modify shared data structures concurrently. The choice between these implementations can dramatically impact your application’s performance, especially under high concurrency. Let’s explore how each implementation works internally and when you should prefer one over the other.

ConcurrentHashMap: Implementation and Performance Characteristics

ConcurrentHashMap is designed for high concurrency and uses a sophisticated locking strategy called “lock striping” to minimize contention between threads. Unlike traditional approaches that use a single lock for the entire map, ConcurrentHashMap divides its internal structure into segments (16 by default), each with its own lock. This means that multiple threads can operate on different segments simultaneously without blocking each other.

How ConcurrentHashMap Works Internally

Under the hood, ConcurrentHashMap uses an array of segments, where each segment is essentially a smaller hash table. When a thread needs to access the map, it first determines which segment the key belongs to by applying a hash function. It then acquires the lock for that specific segment only, rather than locking the entire map. This allows concurrent reads and writes to different segments to proceed in parallel.

The magic of ConcurrentHashMap lies in its clever design:

• Fine-grained locking: Only the segment being accessed is locked
• Optimistic reads: Read operations don’t require locking at all
• CAS operations: Atomic compare-and-swap operations for updates
• Volatile reads: Ensures visibility of changes across threads

Performance Characteristics

ConcurrentHashMap excels in high-concurrency scenarios:

• Excellent read performance: Read operations are nearly as fast as unsynchronized HashMap
• Scalable write performance: Write performance remains good even with many threads
• No blocking reads: Multiple threads can read concurrently without any locks
• Reduced lock contention: Threads working on different parts of the map don’t block each other

According to Baeldung’s benchmarks, ConcurrentHashMap consistently outperforms Collections.synchronizedMap in read-heavy scenarios and scales much better under increasing concurrency. The performance difference becomes particularly noticeable when you have more than a few threads accessing the map concurrently.

Iterator Behavior

One important characteristic of ConcurrentHashMap is that its iterators are “weakly consistent.” This means they reflect the state of the map at some point during iteration but won’t throw ConcurrentModificationException if the map is modified during iteration. This behavior is more forgiving than the traditional fail-fast iterators found in most other collections.

Collections.synchronizedMap: Implementation and Performance Characteristics

Collections.synchronizedMap provides a simpler approach to thread safety by wrapping any Map implementation with a single lock mechanism. When you call Collections.synchronizedMap(new HashMap<>()), you get a thread-safe view of the original Map where all operations are synchronized on a single intrinsic lock.

How synchronizedMap Works Internally

The implementation of Collections.synchronizedMap is straightforward:

• Single lock: All operations are synchronized on a single lock object
• Method-level synchronization: Each public method is synchronized
• External locking: The lock is acquired and released by the synchronizedMap wrapper
• Delegation: All operations are delegated to the underlying Map after acquiring the lock

The simplicity of this approach comes with a significant limitation: every access to the map, whether read or write, must acquire the same single lock. This means that even read operations block each other, which can severely limit performance in read-heavy scenarios.

Performance Characteristics

Collections.synchronizedMap has the following performance characteristics:

• Poor scalability under high concurrency: All threads must compete for the same lock
• Good performance for single-threaded or low-concurrency scenarios: The overhead is minimal when there’s little contention
• Predictable performance: Performance degradation is linear with increasing thread count
• No special optimizations for reads: Even read operations require locking

In scenarios with many threads accessing the map concurrently, Collections.synchronizedMap becomes a significant bottleneck. As Crunchify explains, the single-lock approach means that only one thread can access the map at any given time, regardless of whether it’s reading or writing.

Iterator Behavior

Collections.synchronizedMap provides iterators that are fail-fast. If the map is modified structurally (except through the iterator’s own remove method) while an iteration is in progress, the iterator will throw a ConcurrentModificationException. This behavior helps detect programming errors but can be problematic if modifications during iteration are expected.

Key Differences and When to Use Each Implementation

Lock Granularity

The most fundamental difference between these two implementations is their locking strategy:

• ConcurrentHashMap: Uses lock striping with multiple locks (one per segment)
• Collections.synchronizedMap: Uses a single lock for all operations

This difference has profound implications for performance in concurrent scenarios. With ConcurrentHashMap, multiple threads can safely operate on different segments simultaneously, while with Collections.synchronizedMap, even read operations block each other.

Performance Under Concurrency

Let’s compare how these implementations behave under different concurrency scenarios:

Low Concurrency (1-2 threads):

• Collections.synchronizedMap often performs slightly better due to lower overhead
• The difference is negligible and might favor synchronizedMap

Moderate Concurrency (3-8 threads):

• ConcurrentHashMap starts to show its advantages
• Read operations remain fast for ConcurrentHashMap
• synchronizedMap performance degrades as threads compete for the single lock

High Concurrency (8+ threads):

• ConcurrentHashMap significantly outperforms synchronizedMap
• The difference becomes more pronounced with increasing thread count
• synchronizedMap can become a severe bottleneck

Memory Footprint

ConcurrentHashMap typically has a higher memory footprint than Collections.synchronizedMap due to:

• Additional segment structures
• More complex internal organization
• Optimizations for concurrent access

However, this memory overhead is usually a reasonable trade-off for the significant performance gains in concurrent scenarios.

When to Use ConcurrentHashMap

Choose ConcurrentHashMap when:

• You have multiple threads accessing the map concurrently
• Read operations are frequent or outnumber writes
• You need good scalability as concurrency increases
• You need to iterate over the map while other threads might be modifying it
• Performance is critical under concurrent access

When to Use Collections.synchronizedMap

Choose Collections.synchronizedMap when:

• You have few threads accessing the map (typically 1-2)
• Your codebase needs a simple thread-safe solution
• You’re modifying existing code that already uses a HashMap
• Memory usage is a critical concern
• You need fail-fast iterators for debugging purposes

Performance Comparison and Best Practices

Benchmark Results

Based on various benchmarks (including those from Baeldung and Crunchify), here’s how these implementations typically compare:

Read-Heavy Workloads:

• ConcurrentHashMap: Near-linear scaling with thread count
• Collections.synchronizedMap: Performance degrades significantly with more than a few threads

Write-Heavy Workloads:

• ConcurrentHashMap: Good performance with moderate contention
• Collections.synchronizedMap: Becomes a bottleneck quickly with multiple writers

Mixed Read-Write Workloads:

• ConcurrentHashMap: Maintains reasonable performance
• Collections.synchronizedMap: Performance drops noticeably with mixed access patterns

Best Practices for Using ConcurrentHashMap

1. Prefer ConcurrentHashMap for concurrent access: If you anticipate any concurrent access, ConcurrentHashMap is generally the better choice.

2. Be aware of null values: ConcurrentHashMap doesn’t allow null keys or values, while Collections.synchronizedMap does.

3. Use compute methods for atomic operations: ConcurrentHashMap provides atomic compute, computeIfAbsent, and computeIfPresent methods that are useful for complex operations.

4. Consider size() method: ConcurrentHashMap’s size() method is O(n) in the worst case, while Collections.synchronizedMap’s size() is O(1) but requires locking.

Best Practices for Using Collections.synchronizedMap

1. Use when concurrency is low: If you only have one or two threads accessing the map, the simplicity might be worth the slight performance difference.

2. Manual synchronization for compound operations: For operations that require multiple method calls, you need to manually synchronize on the map to maintain atomicity.

3. Consider creating a synchronized wrapper: If you have an existing HashMap and need thread safety, Collections.synchronizedMap provides a quick solution.

Example Usage

Using ConcurrentHashMap:

// Best for high-concurrency scenarios
Map<String, Integer> concurrentMap = new ConcurrentHashMap<>();
concurrentMap.put("key1", 1);
concurrentMap.putIfAbsent("key2", 2);
// Thread-safe compute operation
concurrentMap.compute("key1", (k, v) -> v + 1);

Using Collections.synchronizedMap:

// Simple thread-safe wrapper
Map<String, Integer> synchronizedMap = Collections.synchronizedMap(new HashMap<>());
synchronizedMap.put("key1", 1);
// For compound operations, you need manual synchronization
synchronized (synchronizedMap) {
 if (synchronizedMap.containsKey("key1")) {
 synchronizedMap.put("key2", synchronizedMap.get("key1") * 2);
 }
}

Sources

1. Crunchify — Performance comparison and technical details between ConcurrentHashMap and synchronizedMap: https://crunchify.com/hashmap-vs-concurrenthashmap-vs-synchronizedmap-how-a-hashmap-can-be-synchronized-in-java/
2. Baeldung — Comprehensive benchmark results and performance metrics: https://www.baeldung.com/java-synchronizedmap-vs-concurrenthashmap
3. Stack Overflow — Technical implementation details and lock striping explanation: https://stackoverflow.com/questions/1291836/concurrenthashmap-vs-synchronized-hashmap
4. HowToDoInJava — Usage scenarios and implementation examples: https://howtodoinjava.com/java/multi-threading/synchronizedmap-vs-concurrenthashmap/
5. Java Revisited — Comparison with other thread-safe collections and locking mechanisms: https://javarevisited.blogspot.com/2011/04/difference-between-ConcurrentHashMap.html
6. Java Code Geeks — Decision guidance and use case recommendations: https://www.javacodegeeks.com/2025/07/concurrenthmap-vs-synchronizedmap-choosing-the-right-tool-for-concurrency.html
7. Stack Overflow — Practical implementation insights and performance degradation patterns: https://stackoverflow.com/questions/510632/whats-the-difference-between-ConcurrentHashMap-and-collections-synchronizedmap
8. HowToDoInJava — Implementation examples and code samples for both approaches: https://howtodoinjava.com/java/collections/hashmap/synchronize-hashmap/

Conclusion

When choosing between ConcurrentHashMap and Collections.synchronizedMap for thread-safe Map implementations in Java, the decision should primarily be based on your expected concurrency requirements. ConcurrentHashMap’s lock striping approach provides superior performance and scalability under high concurrency by allowing multiple threads to access different parts of the map simultaneously. Collections.synchronizedMap, on the other hand, offers a simpler implementation with a single lock that can be sufficient for low-concurrency scenarios or when you need to quickly make an existing HashMap thread-safe.

The performance differences become particularly significant as the number of concurrent threads increases. In modern applications with multiple cores and high concurrency demands, ConcurrentHashMap is generally the better choice for maintaining good performance. However, the simplicity of Collections.synchronizedMap can be appealing for simpler use cases or when you’re working with legacy code. Understanding these differences and their implications is essential for making informed decisions about thread-safe data structures in your Java applications.