Performance

35× faster than the field-leading PHP data-object library — without changing how you write DTOs.

Benchmarked against the most popular full-featured data-object library in the PHP/Laravel ecosystem — identical DTO shapes and attributes, 20,000 iterations per scenario after a 2,000-iteration warmup, PHP 8.4. Absolute numbers vary with hardware; the ratios stay stable across runs.

35×

Hydration throughput

faster on a flat DTO

37×

Serialization throughput

faster on a flat DTO

50×

Peak memory, streaming 50k rows

less with lazyCollection()

Throughput

higher is better · each scenario scaled to its own leader

Hydration — flat DTO35× faster

Simple Data Objects4.5M ops/s

Popular alternative130K ops/s

Hydration — nested DTO30× faster

Simple Data Objects2.2M ops/s

Popular alternative74K ops/s

Hydration — collection of 2036× faster

Simple Data Objects270K ops/s

Popular alternative7.5K ops/s

Serialization — flat DTO37× faster

Simple Data Objects7.4M ops/s

Popular alternative200K ops/s

Serialization — nested DTO34× faster

Simple Data Objects4.0M ops/s

Popular alternative117K ops/s

Peak memory — streaming 50,000 hydrated rows

lower is better

Rows from a generator, consumed one by one.

lazyCollection()50× less memory

Simple Data Objects0.26 MB

Popular alternative13 MB

CPU time per operation follows the same ratios — less CPU burned per request means more headroom per server. The from()/toArray() hot paths execute compiled per-class closures, and lazyCollection() keeps peak memory flat on any dataset size.

The numbers

Scenario	Simple Data Objects	Popular alternative	Advantage
Hydration — flat DTO	~4,500,000 ops/s	~130,000 ops/s	~35×
Hydration — nested DTO	~2,200,000 ops/s	~74,000 ops/s	~30×
Hydration — collection of 20	~270,000 ops/s	~7,500 ops/s	~36×
Serialization — flat DTO	~7,400,000 ops/s	~200,000 ops/s	~37×
Serialization — nested DTO	~4,000,000 ops/s	~117,000 ops/s	~34×
Peak memory — streaming 50,000 rows	0.26 MB	~13 MB	~50×