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Comparison with Immer

Mutative is a high-performance immutable update library, and Immer is a popular immutable update library. This page compares the differences between Mutative and Immer.

Difference between Mutative and Immer

MutativeImmer
Custom shallow copy
Strict mode
No data freeze by default
Non-invasive marking
Complete freeze data
Non-global config
async draft function
Fully compatible with JSON Patch spec
new Set methods(Mutative v1.1.0+)

Mutative has fewer bugs such as accidental draft escapes than Immer, view details.

Mutative vs Immer Performance

Mutative passed all of Immer's test cases.

Measure(ops/sec) to update 50K arrays and 1K objects, bigger is better(view source). [Mutative v1.3.0 vs Immer v10.1.3]

Benchmark

Naive handcrafted reducer - No Freeze x 4,777 ops/sec ±1.06% (94 runs sampled)
Mutative - No Freeze x 6,783 ops/sec ±0.71% (96 runs sampled)
Immer - No Freeze x 5.72 ops/sec ±0.39% (19 runs sampled)

Mutative - Freeze x 1,069 ops/sec ±0.75% (97 runs sampled)
Immer - Freeze x 392 ops/sec ±0.66% (92 runs sampled)

Mutative - Patches and No Freeze x 1,006 ops/sec ±1.73% (95 runs sampled)
Immer - Patches and No Freeze x 5.73 ops/sec ±0.16% (19 runs sampled)

Mutative - Patches and Freeze x 548 ops/sec ±1.06% (94 runs sampled)
Immer - Patches and Freeze x 287 ops/sec ±0.84% (93 runs sampled)

The fastest method is Mutative - No Freeze

Run yarn benchmark to measure performance.

OS: macOS 14.7, CPU: Apple M1 Max, Node.js: v22.11.0

Immer relies on auto-freeze to be enabled, if auto-freeze is disabled, Immer will have a huge performance drop and Mutative will have a huge performance lead, especially with large data structures it will have a performance lead of more than 50x.

So if you are using Immer, you will have to enable auto-freeze for performance. Mutative is disabled auto-freeze by default. With the default configuration of both, we can see the 17x performance gap between Mutative (6,783 ops/sec) and Immer (392 ops/sec).

Overall, Mutative has a huge performance lead over Immer in more performance testing scenarios. Run yarn performance to get all the performance results locally.