Performance and Safety: Choosing Immutable Collections in JavaImmutable collections are a powerful tool in a Java developer’s toolbox. They provide safety guarantees that simplify reasoning about concurrency, reduce bugs caused by unintended mutation, and can sometimes improve performance by enabling safe sharing and avoiding defensive copies. This article explains why immutability matters, compares common immutable-collection options for Java, shows patterns and pitfalls, and gives practical guidance for choosing the right approach for different scenarios.
Why immutability matters
- Safety: Immutable objects can’t be changed after creation, which eliminates a class of bugs where one part of code unexpectedly changes a collection used elsewhere. This is especially valuable in large codebases and library APIs.
- Concurrency: Immutable collections are inherently thread-safe — multiple threads may read them without synchronization because their contents cannot change.
- Simpler reasoning and testing: With immutability, functions that accept collections have fewer side effects to consider; unit tests become easier to write because inputs can be safely reused.
- Safer APIs: Returning immutable collections from methods prevents callers from accidentally altering internal state.
- Potential performance benefits: Because immutable collections are safe to share, you can avoid defensive copying. Persistent (structurally sharing) immutable collections can also make many copy/update operations cheap in terms of allocation and CPU.
Java options for immutable collections
Java developers can choose among several approaches:
- JDK built-in immutable collections (since Java 9)
- Collections.unmodifiable* wrappers (legacy JDK)
- Third-party libraries: Guava, Vavr, Eclipse Collections, PCollections
- Custom defensive-copy patterns
- Persistent data-structure libraries (e.g., PCollections, Cyclops)
Below we compare the most common options.
| Option | Mutability Guarantee | Thread-safety | Structural sharing | Performance notes |
|---|---|---|---|---|
| Java 9+ List.of / Set.of / Map.of | Immutable (throws on mutation) | Thread-safe | No (new instances) | Allocates full structure; cheap for small literals |
| Collections.unmodifiableList / Set / Map | Wrapper only — underlying collection mutable | Not inherently safe if underlying mutated | No | Low overhead for wrapper, but underlying changes reflect |
| Guava ImmutableList / ImmutableMap | Immutable | Thread-safe | No (full copy) | Efficient; optimized builders; good for larger structures |
| Vavr (Persistent collections) | Immutable | Thread-safe | Yes (structural sharing) | Excellent for many updates; functional-style API |
| PCollections | Immutable | Thread-safe | Yes | Persistent, but sometimes slower than Vavr |
| Eclipse Collections Immutable | Immutable | Thread-safe | No | High-performance primitives support |
JDK built-in immutable collections (Java 9+)
Java 9 introduced factory methods such as List.of(…), Set.of(…), and Map.of(…). They offer compact, readable creation of immutable collections and are ideal for small, fixed datasets:
- Creating literals: List.of(“A”, “B”, “C”)
- They throw UnsupportedOperationException on mutation attempts.
- They are space-optimized for small sizes — Map.of has overloads for up to 10 entries and a varargs entry for larger maps.
Use when:
- Collections are fixed at creation and small-to-medium sized.
- You want zero-dependency and clear intent.
Avoid when:
- You need structural sharing for frequent copy-on-write updates.
- You require null keys or values (these factory methods disallow nulls).
Collections.unmodifiable* (legacy wrapper)
Collections.unmodifiableList wraps an existing list and prevents callers from mutating it through the wrapper, but if someone holds a reference to the original collection they can still mutate it.
Use when:
- You have an existing mutable collection you want to expose read-only without copying (but you must ensure no other code mutates it).
- You need minimal overhead and are managing ownership carefully.
Don’t use as a safety substitute for real immutability in multi-component systems unless you can guarantee exclusive ownership.
Guava Immutable* collections
Guava’s ImmutableList, ImmutableSet, and ImmutableMap are widely used. They create true immutable copies and provide builders and efficient factory methods.
Pros:
- True immutability and thread-safety.
- Builders and copyOf convenience methods.
- Well-tested and performant.
Cons:
- Adds dependency (if you don’t already use Guava).
- No structural sharing — full copies on creation.
Use when:
- You need robust, well-documented immutable collections with predictable performance.
- You want builder patterns and advanced utilities (e.g., ordering, multimaps via ImmutableMultimap).
Persistent (structurally sharing) collections: Vavr, PCollections
For workloads that do many small updates while keeping previous versions accessible (functional programming patterns, undo stacks, concurrent snapshots), persistent data structures are the right choice.
- Vavr (formerly Javaslang) provides immutable, persistent List, Map, Set, and many functional utilities. Its collections use structural sharing to keep update costs low.
- PCollections offers persistent implementations like TreePVector, HashPMap.
Pros:
- Efficient copy-on-write semantics via structural sharing.
- Functional API encourages safe, declarative code.
Cons:
- Different performance profile; may be slower for some read-heavy cases compared to arrays or Guava.
- Additional dependency and some API learning curve.
Use when:
- You frequently produce modified versions of collections and need to keep or share previous versions cheaply.
- You’re writing functional-style code or require lock-free snapshots.
Performance considerations
- Allocation patterns: JDK List.of and Guava ImmutableList allocate arrays sized to content, which is fast for small-to-medium collections. Persistent structures allocate smaller nodes and share unchanged parts, which pays off when you do many incremental changes.
- Read throughput: Plain arrays and ArrayList-backed immutable lists typically have the best read performance. Persistent lists may have higher per-access overhead (pointer chasing).
- Update cost: Mutable collections win for in-place updates. Persistent collections and defensive-copy immutable collections cost more at write time but can be cheaper overall when updates are infrequent or when you avoid copying large structures repeatedly.
- Memory: Structural sharing reduces total memory when multiple versions coexist. Full-copy immutables duplicate memory at creation time.
- Cache locality: Flat arrays have better cache locality than node-based persistent structures, affecting CPU-bound loops.
Microbenchmarks can mislead; measure using realistic workloads (JMH). Consider allocation and GC behavior for your environment (latency-sensitive vs throughput).
Practical patterns and recommendations
- Prefer Java 9+ factory methods (List.of, Set.of, Map.of) for small fixed data and configuration constants.
- Use Guava Immutable* for robust, library-grade immutability when dependency is acceptable and you need reliable performance and builders.
- Use persistent collections (Vavr, PCollections) for functional-style code, undo/snapshot requirements, or frequent copy-on-write scenarios.
- Avoid Collections.unmodifiable* as a security boundary; it’s only a shallow read-only view.
- When exposing internal collections from classes, return immutable copies or unmodifiable views of defensive copies to prevent external mutation:
- Best: return true immutable collection (e.g., List.copyOf(…) or Guava ImmutableList.copyOf(…)).
- If performance is critical and you can control callers, document ownership and consider unmodifiable wrappers.
- For mutable builder + immutable result pattern:
- Use a mutable builder (ArrayList, HashMap) for construction, then convert to an immutable instance for publication.
- Example: build with ArrayList, then Collections.unmodifiableList(new ArrayList<>(list)) or List.copyOf(list).
- Favor immutability at API boundaries: it reduces cognitive load for consumers and prevents accidental state corruption.
Example patterns (code)
Builder -> immutable result:
List<String> buildNames() { ArrayList<String> tmp = new ArrayList<>(); tmp.add(...); // many mutations while building return List.copyOf(tmp); // Java 10+; returns an immutable list } Using Guava:
ImmutableList<String> names = ImmutableList.builder() .add("Alice") .addAll(other) .build(); Using Vavr persistent list:
io.vavr.collection.List<String> list = io.vavr.collection.List.empty(); list = list.append("a"); // returns new list, old list is unchanged Pitfalls and gotchas
- Nulls: Many immutable factories (JDK List.of, Guava ImmutableList) disallow nulls. Decide on null-handling strategy early.
- Identity vs equality: Immutable collections may use different implementations with different identity semantics — avoid relying on == for collection comparisons.
- Serialization: Some implementations have special serialization behavior. Confirm compatibility if you serialize objects.
- Large bulk mutations: Repeatedly creating full-copy immutables in tight loops can be costly; consider temporary mutable structures then convert once.
- Third-party library compatibility: Some frameworks expect mutable collections (JPA, certain serializers). Convert at boundaries.
Decision flow (short)
- Are collections fixed and small? -> Java List.of / Set.of
- Need robust API and builders? -> Guava Immutable*
- Need many incremental updates with snapshots? -> Vavr / PCollections
- Exposing internal state but cannot change callers? -> defensive copy to immutable before returning
Conclusion
Immutability improves safety, simplifies concurrency, and can sometimes reduce work by enabling safe sharing. Choose the simplest tool that satisfies your requirements: Java’s built-in immutable factories for constants and small datasets; Guava for production-grade immutability; persistent collections for functional or snapshot-heavy workloads. Always measure in your real workload, pay attention to nulls and serialization, and prefer the builder-then-immutable pattern when construction is complex.
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