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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

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 v1.0.11 vs Immer v10.1.1]

Benchmark

Naive handcrafted reducer - No Freeze x 4,469 ops/sec ±0.82% (99 runs sampled)
Mutative - No Freeze x 6,015 ops/sec ±1.17% (94 runs sampled)
Immer - No Freeze x 5.36 ops/sec ±0.28% (18 runs sampled)

Mutative - Freeze x 959 ops/sec ±0.90% (99 runs sampled)
Immer - Freeze x 382 ops/sec ±0.53% (94 runs sampled)

Mutative - Patches and No Freeze x 970 ops/sec ±0.99% (96 runs sampled)
Immer - Patches and No Freeze x 5.22 ops/sec ±0.80% (18 runs sampled)

Mutative - Patches and Freeze x 505 ops/sec ±0.85% (93 runs sampled)
Immer - Patches and Freeze x 275 ops/sec ±0.49% (89 runs sampled)

The fastest method is Mutative - No Freeze

Run yarn benchmark to measure performance.

OS: macOS 14.6.1, CPU: Apple M1 Max, Node.js: v20.11.0

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 16x performance gap between Mutative (6,015 ops/sec) and Immer (382 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.