The PHP Bench
All runs

20260928011232-b9eaed5b

complete Signed by kaiju · 9f9bb07dedd6...91a4d3d3
Started
Generated
Measured samples
1,872
Combinations
13

Machine

Captured from the runner's system manifest.

Host kaiju Linux · kernel 6.19.8-200.nobara.fc43.x86_64
PHP 8.5.11
Processor Intel(R) Xeon(R) CPU E5-2687W v4 @ 3.00GHz 48 cores · x86_64
Memory 251.7 GB P1_DIMMA1 32 GB 2133 MT/s DDR4 M386A4G40DM0-CPB P1_DIMMB1 32 GB 2133 MT/s DDR4 M386A4G40DM0-CPB P1_DIMMC1 32 GB 2133 MT/s DDR4 M386A4G40DM0-CPB P1_DIMMD1 32 GB 2133 MT/s DDR4 M386A4G40DM0-CPB P2_DIMME1 32 GB 2133 MT/s DDR4 M386A4G40DM0-CPB P2_DIMMF1 32 GB 2133 MT/s DDR4 M386A4G40DM0-CPB P2_DIMMG1 32 GB 2133 MT/s DDR4 M386A4G40DM0-CPB P2_DIMMH1 32 GB 2133 MT/s DDR4 M386A4G40DM0-CPB
Disk 447.1 GB Device: /dev/sda Capacity: 447.1 GB

Runtime envelope

End-to-end time per scenario run across all non-warmup samples on postgresql.

Min sample
101 ms
Mean sample
1,721 ms
Max sample
12,646 ms
Cumulative time
53m 41s
Throughput
0.581/s

Runtime comparison

Mean time per scenario run in this upload, warmup runs excluded, sorted by runtime.

Init Insert Read Update Delete
  1. Cycle 2.16.0 postgresql 878 ms
  2. PHPFUIBatch 3.0.3 postgresql 992 ms
  3. Doctrine 3.6.2 postgresql 1,029 ms
  4. Propel2 6cb272b6 postgresql 1,308 ms
  5. Atlas 2.0.1 postgresql 1,337 ms
  6. ActiveRecord 2.0.6 postgresql 1,487 ms
  7. PHPFUI 3.0.3 postgresql 1,561 ms
  8. Yii 2.0.54 postgresql 1,856 ms
  9. DivergenceV3 3.2.0 postgresql 1,882 ms
  10. CakeCached 5.3.3 postgresql 1,956 ms
  11. Cake 5.3.3 postgresql 1,975 ms
  12. Eloquent 13.2.0 postgresql 2,477 ms
  13. RedBean 5.7.5 postgresql 3,631 ms

Where the time goes

Each bar is one framework's mean scenario run on postgresql, split into its phases and sorted by total. Bars share a scale within each engine. Hover a bar for the numbers.

Init Insert Read Update Delete
Mean split across 13 combinations
Insert 22% Read 11% Update 45% Delete 20%

postgresql

  1. Cycle2.16.0 878 ms
  2. PHPFUIBatch3.0.3 992 ms
  3. Doctrine3.6.2 1,029 ms
  4. Propel26cb272b6 1,308 ms
  5. Atlas2.0.1 1,337 ms
  6. ActiveRecord2.0.6 1,487 ms
  7. PHPFUI3.0.3 1,561 ms
  8. Yii2.0.54 1,856 ms
  9. DivergenceV33.2.0 1,882 ms
  10. CakeCached5.3.3 1,956 ms
  11. Cake5.3.3 1,975 ms
  12. Eloquent13.2.0 2,477 ms
  13. RedBean5.7.5 3,631 ms
Exact numbers
Cycle 2.16.0 postgresql 144 878 ms 229 ms 53.8 ms 343 ms 245 ms
PHPFUIBatch 3.0.3 postgresql 144 992 ms 16.8 ms 177 ms 670 ms 114 ms
Doctrine 3.6.2 postgresql 144 1,029 ms 94.4 ms 168 ms 466 ms 282 ms
Propel2 6cb272b6 postgresql 144 1,308 ms 321 ms 15.4 ms 479 ms 475 ms
Atlas 2.0.1 postgresql 144 1,337 ms 291 ms 155 ms 517 ms 360 ms
ActiveRecord 2.0.6 postgresql 144 1,487 ms 372 ms 210 ms 759 ms 132 ms
PHPFUI 3.0.3 postgresql 144 1,561 ms 305 ms 184 ms 670 ms 388 ms
Yii 2.0.54 postgresql 144 1,856 ms 340 ms 216 ms 777 ms 506 ms
DivergenceV3 3.2.0 postgresql 144 1,882 ms 403 ms 259 ms 824 ms 381 ms
CakeCached 5.3.3 postgresql 144 1,956 ms 484 ms 335 ms 912 ms 220 ms
Cake 5.3.3 postgresql 144 1,975 ms 484 ms 333 ms 931 ms 222 ms
Eloquent 13.2.0 postgresql 144 2,477 ms 390 ms 304 ms 1,116 ms 637 ms
RedBean 5.7.5 postgresql 144 3,631 ms 1,157 ms 193 ms 1,786 ms 488 ms

Scenario families

Mean across every framework and engine in this upload.

  • simple 178 ms
  • string_variable 1,076 ms
  • string_fixed 1,108 ms
  • float_fixed 1,283 ms
  • int_fixed 1,296 ms
  • canary 1,546 ms

What the workloads measure

The row shape and operation mix decide where each framework spends its time.

Scenario families
simple baseline row shape
Shows framework overhead with minimal field complexity, so object creation and query setup dominate.
canary mixed field and nullable stress
Wide mixed records amplify casting, hydration, dirty tracking, and adapter metadata overhead.
int_fixed pure scalar writes
A low-noise floor. Slow results here usually mean framework machinery is expensive even before text and cast-heavy payloads show up.
float_fixed numeric conversion paths
Decimal and float normalization can widen update and verification cost, especially for ORMs that compare serialized values.
string_fixed predictable text hydration
Column count and text assignment matter more than payload variability, which makes hydration strategy easier to isolate.
string_variable application-like text workload
Variable strings and note fields make this the closest to real CRUD traffic and usually punish heavier active-record layers the most.
Operation shapes
Warmup vs hot runs
Run 1 is warmup. Hot-path averages exclude it so boot and metadata setup do not dominate steady-state rankings.
Insert and indexed schemas
Indexed tables make writes cost more because every insert and many updates must maintain secondary indexes as well as the row itself.
Read all vs read probes
Read All rewards bulk hydration efficiency; random and tail probes expose per-query setup, lookup overhead, and tiny-result inefficiency.
Update with verification
Each update shape is followed by a verification read, so dirty-checking, write SQL generation, hydration, and comparison all affect the final time.
Delete with confirmation
Deletes are checked afterward. Frameworks that pay extra for follow-up lookups or teardown lose more time here than a bare SQL path.
Total runtime
The total runtime metric is effectively a benchmark of the machine plus adapter behavior across the full workload, not just one CRUD verb.