TreeMap vs ConcurrentSkipListMap in Java – Ordered Concurrent Maps Compared

Java developers often face the dilemma of choosing the right map implementation when ordering and concurrency are both essential. Two powerful choices in this space are TreeMap and ConcurrentSkipListMap. While both maintain sorted order, only one is built to handle concurrent access out-of-the-box.

Understanding the differences between these two can help you design thread-safe, efficient, and scalable applications without compromising on performance or correctness.

This tutorial will break down both map types, highlighting syntax, use cases, performance, internal structures, and when to use which.

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TreeMap – Ordered But Not Thread-Safe

What Is It?

TreeMap<K, V> is a red-black tree-based implementation of the NavigableMap interface. It keeps keys in natural order or based on a custom Comparator.

Syntax

Map<Integer, String> map = new TreeMap<>();

Key Features

• Keys are always sorted
• Supports methods like headMap(), tailMap(), floorEntry(), etc.
• Not thread-safe — external synchronization is required

Performance

Operation	Time Complexity
get/put/remove	O(log n)
iteration	O(n)

Use Cases

• Sorted leaderboards
• Range queries on data structures
• Non-concurrent search indexes

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ConcurrentSkipListMap – Sorted and Thread-Safe

What Is It?

ConcurrentSkipListMap<K, V> is a concurrent alternative to TreeMap, implementing ConcurrentNavigableMap. It maintains elements in sorted order using skip list data structures.

Syntax

ConcurrentNavigableMap<Integer, String> map = new ConcurrentSkipListMap<>();

Key Features

• Thread-safe and non-blocking
• Maintains key ordering like TreeMap
• Allows concurrent reads and updates

Performance

Operation	Time Complexity
get/put/remove	O(log n)
iteration	O(n)
concurrent access	lock-free (fine-grained)

Use Cases

• Realtime metrics collection
• Concurrent analytics dashboards
• Multi-threaded schedulers

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Core Differences – TreeMap vs ConcurrentSkipListMap

Feature	TreeMap	ConcurrentSkipListMap
Thread-safe	❌ No	✅ Yes
Backing structure	Red-Black Tree	Skip List
Concurrency strategy	Manual sync	Lock-free reads, fine-grained locks
Performance (single thread)	Slightly faster	Slight overhead
Ordering support	✅ Yes	✅ Yes
Concurrent use	❌ Not safe	✅ Designed for it
Iterator fail-fast	✅ Yes (ConcurrentModException)	❌ Weakly consistent

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Code Examples

TreeMap Example

TreeMap<Integer, String> scores = new TreeMap<>();
scores.put(10, "Low");
scores.put(90, "High");
System.out.println(scores.floorEntry(50)); // Output: 10=Low

ConcurrentSkipListMap Example

ConcurrentSkipListMap<Integer, String> map = new ConcurrentSkipListMap<>();
map.put(10, "Task-A");
map.put(20, "Task-B");

map.forEach((k, v) -> System.out.println(k + ": " + v));

With Java 8+ Streams

map.entrySet().stream()
    .filter(e -> e.getKey() > 15)
    .forEach(System.out::println);

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Internal Working

• TreeMap uses a balanced red-black tree where insertions and deletions rebalance the tree to maintain order.
• ConcurrentSkipListMap uses a skip list, a probabilistic data structure layered with multiple levels for efficient traversal.

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Functional Support with Java 8+

Both maps can be used with Streams, Predicate, Function, and Collectors APIs introduced in Java 8.

map.entrySet().stream()
   .filter(entry -> entry.getValue().startsWith("T"))
   .collect(Collectors.toList());

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Java Version Tracker

📌 What's New in Java?

• Java 8
  • Stream API for map entries
  • Functional-style filtering
• Java 9
  • Map.of() for small immutable maps (not for sorted or concurrent)
• Java 10+
  • Type inference via var
• Java 21
  • No direct updates to TreeMap or ConcurrentSkipListMap, but improvements in structured concurrency, virtual threads, and GC boost multi-threaded map performance

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Best Practices

• Prefer TreeMap when working with single-threaded, ordered data
• Use ConcurrentSkipListMap in multi-threaded environments where ordering is required
• Avoid synchronizing access to TreeMap manually — it's error-prone
• Do not mix mutable keys — it breaks ordering and map consistency

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Anti-Patterns

• Using TreeMap in concurrent systems without external locking
• Choosing ConcurrentSkipListMap when you don’t need ordering — ConcurrentHashMap is faster
• Using null keys — both maps disallow null as keys

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Refactoring Legacy Code

• Replace TreeMap + synchronized blocks with ConcurrentSkipListMap
• Replace nested if logic with floorEntry(), ceilingEntry(), and submap methods

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Conclusion and Key Takeaways

• Both TreeMap and ConcurrentSkipListMap maintain sorted order.
• TreeMap is simpler but not thread-safe — ideal for offline or single-threaded apps.
• ConcurrentSkipListMap excels in concurrent environments with high-read/write needs and ordering.
• Choosing the right map ensures correctness, scalability, and maintainability.

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FAQ – TreeMap vs ConcurrentSkipListMap

1. Which map is faster?
   TreeMap is faster in single-threaded use; ConcurrentSkipListMap scales better with threads.

2. Can I use null keys?
   No. Both maps throw NullPointerException for null keys.

3. Is ConcurrentSkipListMap lock-free?
   It uses fine-grained locking, making reads mostly lock-free.

4. Can I iterate while modifying the map?
   TreeMap throws ConcurrentModificationException; ConcurrentSkipListMap allows safe iteration.

5. Are views like subMap and headMap safe concurrently?
   Yes, in ConcurrentSkipListMap. Not in TreeMap.

6. Is ConcurrentSkipListMap backed by a tree?
   No, it uses a skip list.

7. Should I replace HashMap with TreeMap?
   Only if ordering is required. Otherwise, HashMap is faster.

8. Can I get reverse order in both maps?
   Yes. Use descendingMap().

9. Are these maps serializable?
   Yes.

10. Is performance O(log n) in both?
    Yes — due to red-black tree and skip list structures.

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