trevordilley/ecs-benchmark

ECS benchmark comparison

ECS benchmark comparison

A suite of benchmarks designed to test and compare JavaScript ECS library performance across a variety of challenging circumstances.

SoA implementations

op/s	packed_5	simple_iter	frag_iter	entity_cycle	add_remove
bitecs	335,064	115,954	431,207	1,634	2,334
harmony-ecs	313,278	132,026	489,903	4,040	4,194
piecs	364,652	177,269	470,904	64,075	20,649
wolf-ecs	378,471	165,951	535,362	2,597	3,913

Object-based implementations

op/s	packed_5	simple_iter	frag_iter	entity_cycle	add_remove
becsy	103,417	28,337	61,296	692	8,953
ecsy	7,822	4,822	24,537	120	975
geotic	45,957	29,631	49,482	106	1,099
goodluck	53,927	31,894	77,575	27,253	301,727
javelin-ecs	65,990	38,474	121,207	656	3,286
miniplex	109,296	36,316	20,372	310	6,645
perform-ecs	55,241	94,791	31,170	159	442
picoes	6,814	4,223	12,368	2,679	4,303
tiny-ecs	16,391	35,488	45,760	194	1,082
uecs	29,855	14,747	9,861	1,724	5,207

The best result for each benchmark is marked in bold text. Note that run to run variance for these benchmarks is typically 1-4%. Any benchmarks within a few percent of each other should be considered “effectively equal”. The above benchmarks are run on node v17.8.0.

Frameworks

• @javelin/ecs
• @lastolivegames/becsy
• bitecs
• ecsy
• harmony-ecs
• geotic
• goodluck
• miniplex
• perform-ecs
• picoes
• piecs
• tiny-ecs
• uecs
• wolf-ecs

Benchmarks

Packed Iteration (5 queries)

This benchmark is designed to test the core overheads involved in component iteration when multiple queries are run.

• Dataset: 1,000 entities, each with (A, B, C, D, E) components.
• Test:
  • Iterate through all entities with A and double its value.
  • Iterate through all entities with B and double its value.
  • Iterate through all entities with C and double its value.
  • Iterate through all entities with D and double its value.
  • Iterate through all entities with E and double its value.

Simple Iteration

This benchmark is designed to test how efficiently the ECS can run multiple independent systems.

• Dataset:
  • 1,000 entities with (A, B) components
  • 1,000 entities with (A, B, C) components
  • 1,000 entities with (A, B, C, D) components
  • 1,000 entities with (A, B, C, E) components
• Test: Three systems accessing the following components, where each system swaps the values stored in each component:
  • (A, B)
  • (C, D)
  • (C, E)

Fragmented Iteration

This benchmark is designed to test how the ECS handles iteration through a fragmented dataset.

• Dataset: 26 component types (A through Z), each with 100 entities plus a Data component.
• Test:
  • Iterate through all entities with a Data component and double its value.
  • Iterate through all entities with a Z component and double its value.

Entity Cycle

This benchmark is designed to test the base cost of constructing and destroying entities into the ECS.

• Dataset: 1,000 entities with a single A component.
• Test: Iterate through all entities, and create 1 entity with a B component. Then iterate through all entities with a B component and destroy them.

Add / Remove

This benchmark is designed to test how quickly the ECS can add and then remove a component from an existing entity.

• Dataset: 1,000 entities with a single A component.
• Test: Iterate through all entities, adding a B component. Then iterate through all entities again, removing their B component.