The PHP Bench
All runs

20260329203643-74505162

complete Signed by runner-20260329222123 · 409ffba3dd66...5ffbf106
Started
Generated
Measured samples
78
Combinations
13

Machine

Captured from the runner's system manifest.

Host eimu Linux · kernel 6.19.6
PHP 8.5.3
Processor AMD Ryzen 9 5950X 16-Core Processor 32 cores · x86_64
Memory 31.2 GB DIMM_A2 16 GiB 2666 MT/s DDR4 F4-4266C19-16GVK DIMM_B2 16 GiB 2666 MT/s DDR4 F4-4266C19-16GVK
Disk 3.5 TB Device: /dev/nvme0n1 Capacity: 3.5 TB

Runtime envelope

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

Min sample
73.0 ms
Mean sample
142 ms
Max sample
432 ms
Cumulative time
11.109s
Throughput
7.021/s

Runtime comparison

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

Init Insert Read Update Delete
  1. Atlas 2.0.1 sqlite-file 85.9 ms
  2. Doctrine 3.6.2 sqlite-file 101 ms
  3. PHPFUIBatch 3.0.3 sqlite-file 102 ms
  4. Cycle 2.16.0 sqlite-file 115 ms
  5. ActiveRecord 2.0.6 sqlite-file 119 ms
  6. PHPFUI 3.0.3 sqlite-file 123 ms
  7. Propel2 6cb272b6 sqlite-file 140 ms
  8. CakeCached 5.3.3 sqlite-file 147 ms
  9. Cake 5.3.3 sqlite-file 148 ms
  10. Yii 2.0.54 sqlite-file 151 ms
  11. RedBean 5.7.5 sqlite-file 160 ms
  12. DivergenceV3 3.2.0 sqlite-file 161 ms
  13. Eloquent 13.2.0 sqlite-file 297 ms

Where the time goes

Each bar is one framework's mean scenario run on sqlite-file, 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
Init 13% Insert 18% Read 9% Update 54%

sqlite-file

  1. Atlas2.0.1 85.9 ms
  2. Doctrine3.6.2 101 ms
  3. PHPFUIBatch3.0.3 102 ms
  4. Cycle2.16.0 115 ms
  5. ActiveRecord2.0.6 119 ms
  6. PHPFUI3.0.3 123 ms
  7. Propel26cb272b6 140 ms
  8. CakeCached5.3.3 147 ms
  9. Cake5.3.3 148 ms
  10. Yii2.0.54 151 ms
  11. RedBean5.7.5 160 ms
  12. DivergenceV33.2.0 161 ms
  13. Eloquent13.2.0 297 ms
Exact numbers
Atlas 2.0.1 sqlite-file 6 85.9 ms 11.7 ms 4.78 ms 58.0 ms 10.1 ms
Doctrine 3.6.2 sqlite-file 6 101 ms 21.8 ms 16.9 ms 17.6 ms 1.38 ms
PHPFUIBatch 3.0.3 sqlite-file 6 102 ms 8.22 ms 5.85 ms 82.8 ms 2.72 ms
Cycle 2.16.0 sqlite-file 6 115 ms 14.2 ms 4.84 ms 69.5 ms 12.7 ms
ActiveRecord 2.0.6 sqlite-file 6 119 ms 22.6 ms 12.2 ms 80.0 ms 2.03 ms
PHPFUI 3.0.3 sqlite-file 6 123 ms 17.8 ms 6.53 ms 81.9 ms 14.4 ms
Propel2 6cb272b6 sqlite-file 6 140 ms 21.8 ms 12.0 ms 84.2 ms 14.9 ms
CakeCached 5.3.3 sqlite-file 6 147 ms 48.1 ms 19.8 ms 60.3 ms 5.32 ms
Cake 5.3.3 sqlite-file 6 148 ms 49.3 ms 20.2 ms 60.2 ms 4.63 ms
Yii 2.0.54 sqlite-file 6 151 ms 24.7 ms 18.3 ms 85.5 ms 13.0 ms
RedBean 5.7.5 sqlite-file 6 160 ms 22.6 ms 6.87 ms 97.6 ms 15.5 ms
DivergenceV3 3.2.0 sqlite-file 6 161 ms 25.5 ms 15.3 ms 104 ms 13.9 ms
Eloquent 13.2.0 sqlite-file 6 297 ms 52.5 ms 23.9 ms 163 ms 18.2 ms

Scenario families

Mean across every framework and engine in this upload.

  • simple 99.7 ms
  • string_fixed 119 ms
  • string_variable 122 ms
  • int_fixed 124 ms
  • float_fixed 141 ms
  • canary 154 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.