diff --git a/README.md b/README.md
index 99fb821e..214a180c 100644
--- a/README.md
+++ b/README.md
@@ -110,8 +110,10 @@ Full semantics: [Outcomes & Delivery](https://shove.rs/concepts/outcomes).
The charts are generated from a committed results document — never hand-copied —
and each one carries its own provenance (shove version, generation date,
hardware) in the caption. The harness runs against every backend; the currently
-published document measures the in-process and Kafka backends, and a plotted
-series appears only for a backend the document actually contains. See
+published document measures the in-process, Kafka, RabbitMQ and Redis backends,
+and a plotted series appears only for a backend the document actually contains.
+NATS is absent until a publisher fix lands, and SQS is absent because it runs only
+against LocalStack. See
[Measurement methodology](https://shove.rs/ops/performance#measurement-methodology)
for what is measured and what is still pending.
diff --git a/benches/results/bench-results.json b/benches/results/bench-results.json
index cb7bc260..f182af53 100644
--- a/benches/results/bench-results.json
+++ b/benches/results/bench-results.json
@@ -1,6 +1,6 @@
{
"schema_version": 6,
- "generated_at": "2026-09-04T13:16:16Z",
+ "generated_at": "2026-09-07T13:47:38Z",
"shove_version": "0.14.0",
"rust_version": "rustc 1.91.1 (ed61e7d7e 2025-11-07)",
"hardware": {
@@ -6076,7 +6076,7 @@
"peak_rss_mb": 4.578125,
"cpu_pct": 12.83364572988269,
"duration_secs": 10.000727708,
- "setup_secs": 3.1816746670000002,
+ "setup_secs": 3.181674667,
"load": {
"offered_msg_per_sec": 25000,
"window_secs": 10,
@@ -6182,7 +6182,7 @@
"e2e_p99_ms": 12.705292,
"scaling_efficiency": 1.0,
"peak_rss_mb": 0.1875,
- "cpu_pct": 11.398452813622649,
+ "cpu_pct": 11.398452813622647,
"duration_secs": 10.009347208,
"setup_secs": 3.181928542,
"load": {
@@ -6266,7 +6266,7 @@
"published": 999388,
"published_at_window_end": 999388,
"processed_at_window_end": 999303,
- "achieved_publish_msg_per_sec": 99898.17141368607,
+ "achieved_publish_msg_per_sec": 99898.17141368608,
"lag_at_window_end": 85,
"peak_lag": 3394,
"drain_secs": 0.0113625,
@@ -6392,7 +6392,7 @@
"consumers": 1,
"handler": "zero (no-op)",
"handler_cost": "setup_bound",
- "throughput_msg_per_sec": 1556.6781051259675,
+ "throughput_msg_per_sec": 1556.6781051259677,
"dispatch_p50_ms": 3148.898334,
"dispatch_p95_ms": 3201.462916,
"dispatch_p99_ms": 3204.107166,
@@ -6423,7 +6423,7 @@
"e2e_p99_ms": 3212.706875,
"scaling_efficiency": 1.0,
"peak_rss_mb": 0.09375,
- "cpu_pct": 0.020486444414497578,
+ "cpu_pct": 0.020486444414497575,
"duration_secs": 3.221589958,
"setup_secs": null
},
@@ -6505,7 +6505,7 @@
"e2e_p99_ms": 120.01075,
"scaling_efficiency": 1.0,
"peak_rss_mb": 0.046875,
- "cpu_pct": 10.730559690264533,
+ "cpu_pct": 10.730559690264531,
"duration_secs": 10.003985,
"setup_secs": 3.440648667,
"load": {
@@ -6658,7 +6658,7 @@
"e2e_p99_ms": 128.222125,
"scaling_efficiency": 1.0,
"peak_rss_mb": 0.015625,
- "cpu_pct": 11.211687688561247,
+ "cpu_pct": 11.211687688561248,
"duration_secs": 10.004110541,
"setup_secs": 3.425400041,
"load": {
@@ -6727,7 +6727,7 @@
"handler_cost": "framework",
"max_batch_size": 500,
"max_batch_age_ms": 250,
- "throughput_msg_per_sec": 99859.44749778083,
+ "throughput_msg_per_sec": 99859.44749778084,
"dispatch_p50_ms": 10.381666,
"dispatch_p95_ms": 20.386042,
"dispatch_p99_ms": 65.834292,
@@ -6738,7 +6738,7 @@
"peak_rss_mb": 0.109375,
"cpu_pct": 23.211558003677688,
"duration_secs": 10.004060958,
- "setup_secs": 3.4373713329999998,
+ "setup_secs": 3.437371333,
"load": {
"offered_msg_per_sec": 100000,
"window_secs": 10,
@@ -6746,7 +6746,7 @@
"published": 999628,
"published_at_window_end": 999628,
"processed_at_window_end": 999000,
- "achieved_publish_msg_per_sec": 99922.22200531697,
+ "achieved_publish_msg_per_sec": 99922.22200531696,
"lag_at_window_end": 628,
"peak_lag": 9339,
"drain_secs": 0.257024917,
@@ -6850,7 +6850,7 @@
"e2e_p99_ms": 7013.979333,
"scaling_efficiency": 1.0,
"peak_rss_mb": 185.84375,
- "cpu_pct": 232.25614920866118,
+ "cpu_pct": 232.2561492086612,
"duration_secs": 10.229543958,
"setup_secs": 3.429176583,
"load": {
@@ -6921,7 +6921,7 @@
"e2e_p99_ms": 12.040083,
"scaling_efficiency": 1.0,
"peak_rss_mb": 0.03125,
- "cpu_pct": 10.972972137599653,
+ "cpu_pct": 10.972972137599651,
"duration_secs": 10.0059645,
"setup_secs": 3.642154417,
"load": {
@@ -6958,7 +6958,7 @@
"e2e_p99_ms": 16.539208,
"scaling_efficiency": 1.0,
"peak_rss_mb": 0.0,
- "cpu_pct": 13.416394954940113,
+ "cpu_pct": 13.416394954940111,
"duration_secs": 10.00617525,
"setup_secs": 3.494536584,
"load": {
@@ -6986,7 +6986,7 @@
"consumers": 1,
"handler": "zero (no-op)",
"handler_cost": "framework",
- "throughput_msg_per_sec": 99876.55095650641,
+ "throughput_msg_per_sec": 99876.5509565064,
"dispatch_p50_ms": 8.208583,
"dispatch_p95_ms": 13.212833,
"dispatch_p99_ms": 19.838083,
@@ -7005,7 +7005,7 @@
"published": 999677,
"published_at_window_end": 999677,
"processed_at_window_end": 999434,
- "achieved_publish_msg_per_sec": 99900.83470298935,
+ "achieved_publish_msg_per_sec": 99900.83470298936,
"lag_at_window_end": 243,
"peak_lag": 4803,
"drain_secs": 0.012055417,
@@ -7066,7 +7066,7 @@
"e2e_p99_ms": 13.743125,
"scaling_efficiency": 1.0,
"peak_rss_mb": 0.0625,
- "cpu_pct": 11.499996972162455,
+ "cpu_pct": 11.499996972162457,
"duration_secs": 10.0031135,
"setup_secs": 3.605212875,
"load": {
@@ -7140,7 +7140,7 @@
"e2e_p99_ms": 22.617917,
"scaling_efficiency": 1.0,
"peak_rss_mb": 0.0,
- "cpu_pct": 23.285604818190926,
+ "cpu_pct": 23.28560481819093,
"duration_secs": 10.005208542,
"setup_secs": 3.598662792,
"load": {
@@ -7298,7 +7298,7 @@
"consumers": 1,
"handler": "zero (no-op)",
"handler_cost": "setup_bound",
- "throughput_msg_per_sec": 48417.670346412844,
+ "throughput_msg_per_sec": 48417.67034641285,
"dispatch_p50_ms": 16.52375,
"dispatch_p95_ms": 28.577833,
"dispatch_p99_ms": 29.27425,
@@ -7351,7 +7351,7 @@
"e2e_p99_ms": 3231.203709,
"scaling_efficiency": 1.0,
"peak_rss_mb": 0.09375,
- "cpu_pct": 0.019247620405372246,
+ "cpu_pct": 0.01924762040537225,
"duration_secs": 3.236748,
"setup_secs": null
},
@@ -7386,7 +7386,7 @@
"consumers": 1,
"handler": "zero (no-op)",
"handler_cost": "setup_bound",
- "throughput_msg_per_sec": 1482.1947465311735,
+ "throughput_msg_per_sec": 1482.1947465311737,
"dispatch_p50_ms": 3293.131458,
"dispatch_p95_ms": 3356.032375,
"dispatch_p99_ms": 3362.120208,
@@ -7668,7 +7668,7 @@
"e2e_p50_ms": 7.872,
"e2e_p95_ms": 12.64675,
"e2e_p99_ms": 21.090083,
- "scaling_efficiency": 0.9999257141854403,
+ "scaling_efficiency": 0.9999257141854404,
"peak_rss_mb": 0.015625,
"cpu_pct": 22.103753555150092,
"duration_secs": 10.003318459,
@@ -7853,7 +7853,7 @@
"e2e_p99_ms": 221.730917,
"scaling_efficiency": 1.0000622174932956,
"peak_rss_mb": 0.046875,
- "cpu_pct": 11.498403139822639,
+ "cpu_pct": 11.49840313982264,
"duration_secs": 10.003968917,
"setup_secs": 6.436844375,
"load": {
@@ -7883,14 +7883,14 @@
"handler_cost": "framework",
"max_batch_size": 500,
"max_batch_age_ms": 250,
- "throughput_msg_per_sec": 24885.434659612554,
+ "throughput_msg_per_sec": 24885.43465961255,
"dispatch_p50_ms": 26.523,
"dispatch_p95_ms": 50.653375,
"dispatch_p99_ms": 63.951584,
"e2e_p50_ms": 26.544333,
"e2e_p95_ms": 50.670583,
"e2e_p99_ms": 63.959042,
- "scaling_efficiency": 0.9977517383009353,
+ "scaling_efficiency": 0.9977517383009352,
"peak_rss_mb": 0.03125,
"cpu_pct": 12.402631358621084,
"duration_secs": 10.005852958,
@@ -7971,7 +7971,7 @@
"scaling_efficiency": 2.1416054082333917,
"peak_rss_mb": 241.53125,
"cpu_pct": 0.0,
- "duration_secs": 15.387142666999999,
+ "duration_secs": 15.387142667,
"setup_secs": 6.190348375,
"method": "drain",
"drain": {
@@ -8004,7 +8004,7 @@
"e2e_p50_ms": 106.791208,
"e2e_p95_ms": 202.142125,
"e2e_p99_ms": 224.77725,
- "scaling_efficiency": 0.9990997962389827,
+ "scaling_efficiency": 0.9990997962389828,
"peak_rss_mb": 0.015625,
"cpu_pct": 11.044426169043724,
"duration_secs": 10.007055833,
@@ -8043,7 +8043,7 @@
"e2e_p50_ms": 26.255417,
"e2e_p95_ms": 50.128666,
"e2e_p99_ms": 61.02175,
- "scaling_efficiency": 0.9998360231331451,
+ "scaling_efficiency": 0.9998360231331452,
"peak_rss_mb": 0.0,
"cpu_pct": 17.495009002579582,
"duration_secs": 10.007644,
@@ -8075,14 +8075,14 @@
"handler_cost": "framework",
"max_batch_size": 500,
"max_batch_age_ms": 250,
- "throughput_msg_per_sec": 99856.29290059741,
+ "throughput_msg_per_sec": 99856.2929005974,
"dispatch_p50_ms": 12.743375,
"dispatch_p95_ms": 21.939083,
"dispatch_p99_ms": 35.047917,
"e2e_p50_ms": 12.763708,
"e2e_p95_ms": 21.956791,
"e2e_p99_ms": 35.056708,
- "scaling_efficiency": 0.9999684096271063,
+ "scaling_efficiency": 0.9999684096271064,
"peak_rss_mb": 0.015625,
"cpu_pct": 28.72553319689044,
"duration_secs": 10.004377,
@@ -8412,9 +8412,9 @@
"e2e_p50_ms": 6.540833,
"e2e_p95_ms": 8.629625,
"e2e_p99_ms": 12.141084,
- "scaling_efficiency": 0.9996739507587715,
+ "scaling_efficiency": 0.9996739507587716,
"peak_rss_mb": 0.015625,
- "cpu_pct": 11.984601539056877,
+ "cpu_pct": 11.984601539056875,
"duration_secs": 10.005975584,
"setup_secs": 6.655422709,
"load": {
@@ -8479,7 +8479,7 @@
"consumers": 2,
"handler": "zero (no-op)",
"handler_cost": "framework",
- "throughput_msg_per_sec": 99865.89096726655,
+ "throughput_msg_per_sec": 99865.89096726656,
"dispatch_p50_ms": 7.952875,
"dispatch_p95_ms": 13.800583,
"dispatch_p99_ms": 30.282,
@@ -8646,7 +8646,7 @@
"consumers": 2,
"handler": "zero (no-op)",
"handler_cost": "setup_bound",
- "throughput_msg_per_sec": 103100.71056803523,
+ "throughput_msg_per_sec": 103100.71056803524,
"dispatch_p50_ms": 13.578041,
"dispatch_p95_ms": 23.669708,
"dispatch_p99_ms": 25.358041,
@@ -8770,7 +8770,7 @@
"e2e_p99_ms": 11.1325,
"scaling_efficiency": 1.0003286693715656,
"peak_rss_mb": 0.0,
- "cpu_pct": 11.380680675391059,
+ "cpu_pct": 11.38068067539106,
"duration_secs": 10.006131,
"setup_secs": 6.881353625,
"load": {
@@ -8817,7 +8817,7 @@
"published": 999562,
"published_at_window_end": 999562,
"processed_at_window_end": 999502,
- "achieved_publish_msg_per_sec": 99885.86121557323,
+ "achieved_publish_msg_per_sec": 99885.86121557324,
"lag_at_window_end": 60,
"peak_lag": 4174,
"drain_secs": 0.011925875,
@@ -8913,7 +8913,7 @@
"e2e_p50_ms": 7.398833,
"e2e_p95_ms": 11.371,
"e2e_p99_ms": 16.587167,
- "scaling_efficiency": 1.0000106024782587,
+ "scaling_efficiency": 1.000010602478259,
"peak_rss_mb": 0.0,
"cpu_pct": 17.627230663380054,
"duration_secs": 10.005518125,
@@ -8950,7 +8950,7 @@
"e2e_p50_ms": 8.002792,
"e2e_p95_ms": 11.267833,
"e2e_p99_ms": 22.490667,
- "scaling_efficiency": 0.9997971760533483,
+ "scaling_efficiency": 0.9997971760533484,
"peak_rss_mb": 0.015625,
"cpu_pct": 26.2471406454947,
"duration_secs": 10.00477475,
@@ -8962,7 +8962,7 @@
"published": 999534,
"published_at_window_end": 999534,
"processed_at_window_end": 999171,
- "achieved_publish_msg_per_sec": 99905.69752707327,
+ "achieved_publish_msg_per_sec": 99905.69752707328,
"lag_at_window_end": 363,
"peak_lag": 3789,
"drain_secs": 0.011453083,
@@ -8987,7 +8987,7 @@
"e2e_p50_ms": 0.0,
"e2e_p95_ms": 0.0,
"e2e_p99_ms": 0.0,
- "scaling_efficiency": 1.7492755324158857,
+ "scaling_efficiency": 1.7492755324158855,
"peak_rss_mb": 6.0625,
"cpu_pct": 0.0,
"duration_secs": 0.519439042,
@@ -9135,7 +9135,7 @@
"e2e_p99_ms": 258.461958,
"scaling_efficiency": 0.999813249974274,
"peak_rss_mb": 0.03125,
- "cpu_pct": 10.963953344153337,
+ "cpu_pct": 10.963953344153335,
"duration_secs": 10.005449292,
"setup_secs": 6.477287666,
"load": {
@@ -9172,7 +9172,7 @@
"e2e_p50_ms": 44.940833,
"e2e_p95_ms": 95.820541,
"e2e_p99_ms": 130.177291,
- "scaling_efficiency": 0.9960467053039601,
+ "scaling_efficiency": 0.99604670530396,
"peak_rss_mb": 0.015625,
"cpu_pct": 13.34824615084761,
"duration_secs": 10.0026935,
@@ -9211,9 +9211,9 @@
"e2e_p50_ms": 15.62325,
"e2e_p95_ms": 37.427792,
"e2e_p99_ms": 51.890959,
- "scaling_efficiency": 0.9988686505000143,
+ "scaling_efficiency": 0.9988686505000144,
"peak_rss_mb": 0.046875,
- "cpu_pct": 20.375662675219758,
+ "cpu_pct": 20.37566267521976,
"duration_secs": 10.006276083,
"setup_secs": 6.431085375,
"load": {
@@ -9286,7 +9286,7 @@
"e2e_p50_ms": 135.900375,
"e2e_p95_ms": 251.016917,
"e2e_p99_ms": 258.88425,
- "scaling_efficiency": 1.0015905128737461,
+ "scaling_efficiency": 1.001590512873746,
"peak_rss_mb": 0.0,
"cpu_pct": 11.771947226950944,
"duration_secs": 10.004770291,
@@ -9325,7 +9325,7 @@
"e2e_p50_ms": 45.015709,
"e2e_p95_ms": 95.987458,
"e2e_p99_ms": 119.772583,
- "scaling_efficiency": 1.0000425907370853,
+ "scaling_efficiency": 1.0000425907370851,
"peak_rss_mb": 0.0,
"cpu_pct": 17.77855185888089,
"duration_secs": 10.005576833,
@@ -9337,7 +9337,7 @@
"published": 249940,
"published_at_window_end": 249940,
"processed_at_window_end": 249497,
- "achieved_publish_msg_per_sec": 24980.069032667638,
+ "achieved_publish_msg_per_sec": 24980.06903266764,
"lag_at_window_end": 443,
"peak_lag": 2124,
"drain_secs": 0.256232042,
@@ -9364,9 +9364,9 @@
"e2e_p50_ms": 15.898791,
"e2e_p95_ms": 37.901458,
"e2e_p99_ms": 53.248458,
- "scaling_efficiency": 0.9991497310102715,
+ "scaling_efficiency": 0.9991497310102716,
"peak_rss_mb": 0.0,
- "cpu_pct": 26.675654538146258,
+ "cpu_pct": 26.675654538146254,
"duration_secs": 10.007563041,
"setup_secs": 6.444197917,
"load": {
@@ -9439,7 +9439,7 @@
"e2e_p50_ms": 135.906791,
"e2e_p95_ms": 251.875375,
"e2e_p99_ms": 261.848084,
- "scaling_efficiency": 0.9935790146200791,
+ "scaling_efficiency": 0.9935790146200792,
"peak_rss_mb": 0.0,
"cpu_pct": 34.827457848607125,
"duration_secs": 10.125794958,
@@ -9551,7 +9551,7 @@
"e2e_p99_ms": 11.484167,
"scaling_efficiency": 1.0000863176841246,
"peak_rss_mb": 0.015625,
- "cpu_pct": 11.300111054439181,
+ "cpu_pct": 11.30011105443918,
"duration_secs": 10.003299208,
"setup_secs": 6.619226792,
"load": {
@@ -9635,7 +9635,7 @@
"published": 999799,
"published_at_window_end": 999799,
"processed_at_window_end": 999661,
- "achieved_publish_msg_per_sec": 99912.58389659967,
+ "achieved_publish_msg_per_sec": 99912.58389659968,
"lag_at_window_end": 138,
"peak_lag": 1526,
"drain_secs": 0.012495416,
@@ -9694,7 +9694,7 @@
"e2e_p50_ms": 6.603417,
"e2e_p95_ms": 9.514333,
"e2e_p99_ms": 12.36225,
- "scaling_efficiency": 0.9998775060468721,
+ "scaling_efficiency": 0.999877506046872,
"peak_rss_mb": 0.0,
"cpu_pct": 12.116923759061113,
"duration_secs": 10.006341,
@@ -9768,7 +9768,7 @@
"e2e_p50_ms": 7.951416,
"e2e_p95_ms": 11.755958,
"e2e_p99_ms": 22.714875,
- "scaling_efficiency": 0.9997893369056345,
+ "scaling_efficiency": 0.9997893369056344,
"peak_rss_mb": 0.03125,
"cpu_pct": 26.57409539947991,
"duration_secs": 10.007587083,
@@ -9780,7 +9780,7 @@
"published": 999679,
"published_at_window_end": 999679,
"processed_at_window_end": 999394,
- "achieved_publish_msg_per_sec": 99892.11102625985,
+ "achieved_publish_msg_per_sec": 99892.11102625984,
"lag_at_window_end": 285,
"peak_lag": 4084,
"drain_secs": 0.01258725,
@@ -9876,7 +9876,7 @@
"e2e_p50_ms": 257.320916,
"e2e_p95_ms": 680.789041,
"e2e_p99_ms": 876.818125,
- "scaling_efficiency": 1.7986137541060903,
+ "scaling_efficiency": 1.7986137541060905,
"peak_rss_mb": 8.296875,
"cpu_pct": 322.3452077874202,
"duration_secs": 10.290763416,
@@ -9957,7 +9957,7 @@
"e2e_p50_ms": 113.471583,
"e2e_p95_ms": 191.017375,
"e2e_p99_ms": 222.175,
- "scaling_efficiency": 3.6098868853548165,
+ "scaling_efficiency": 3.609886885354817,
"peak_rss_mb": 0.0,
"cpu_pct": 0.0,
"duration_secs": 0.982899958,
@@ -10080,7 +10080,7 @@
"consumers": 8,
"handler": "zero (no-op)",
"handler_cost": "framework",
- "throughput_msg_per_sec": 99896.93940748267,
+ "throughput_msg_per_sec": 99896.93940748269,
"dispatch_p50_ms": 7.836666,
"dispatch_p95_ms": 12.767333,
"dispatch_p99_ms": 17.696208,
@@ -10099,7 +10099,7 @@
"published": 999603,
"published_at_window_end": 999603,
"processed_at_window_end": 999521,
- "achieved_publish_msg_per_sec": 99905.13488214645,
+ "achieved_publish_msg_per_sec": 99905.13488214643,
"lag_at_window_end": 82,
"peak_lag": 4697,
"drain_secs": 0.012308958,
@@ -10158,7 +10158,7 @@
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+ "consumers": 8,
+ "handler": "zero (no-op)",
+ "error": "topology error: topic 'shove-stress-bench-seq' is sequenced; `concurrent_processing` on a FIFO consumer would break per-key ordering. Drop `with_concurrent_processing(true)` or use `register` for unsequenced topics."
+ },
+ {
+ "flow": "consume_batch",
+ "mode": "batch",
+ "payload_bytes": 64,
+ "tier": "moderate",
+ "messages": 6000000,
+ "consumers": 1,
+ "handler": "zero (no-op)",
+ "method": "drain",
+ "error": "purge: DEL: timed out"
+ }
+ ],
+ "unsupported": []
}
]
}
diff --git a/docs/pages/ops/performance.mdx b/docs/pages/ops/performance.mdx
index 046e7b5a..4204b587 100644
--- a/docs/pages/ops/performance.mdx
+++ b/docs/pages/ops/performance.mdx
@@ -10,13 +10,14 @@ an explicit "not supported" marker, never as a zero. And a backend the results
document does not contain is never plotted, so absence from a chart means "not
measured here", not "slow".
-The document these charts render from measures the **in-process** and **Kafka**
-backends. NATS, RabbitMQ and Redis are supported by the harness but are not in
-this document yet; SQS additionally only runs against LocalStack
-(non-representative by design), which needs a LocalStack Pro auth token. The
-harness refuses to merge runs measured on different hosts into one document, so
-completing the set means re-measuring every backend back to back on a single
-host rather than appending to what is published here — that rerun is pending.
+The document these charts render from measures the **in-process**, **Kafka**,
+**RabbitMQ** and **Redis** backends. NATS is supported by the harness but is not
+in this document yet: the drain fill deadlocks in the NATS publisher's in-flight
+ack budget, and the run waits on that fix. SQS only runs against LocalStack
+(non-representative by design), needs a LocalStack Pro auth token, and is not in
+this document either. The harness refuses to merge runs measured on different
+hosts into one document, so completing the set means measuring the remaining
+backends on the same host as the published runs.
### Throughput vs consumer count
diff --git a/docs/public/bench/dispatch-latency-1kib-dark.svg b/docs/public/bench/dispatch-latency-1kib-dark.svg
index d05604e2..4868aa27 100644
--- a/docs/public/bench/dispatch-latency-1kib-dark.svg
+++ b/docs/public/bench/dispatch-latency-1kib-dark.svg
@@ -7,102 +7,183 @@ Dispatch latency percentiles
consume_parallel — 1 KiB payload — sustained offered load — lower is better
-
+
dispatch = publish → handler entry, measured while a paced producer held the offered rate and the consumers kept up (a
-
+
sustained offered-load rung); the backlog a corpus-mode row would add is absent by construction
+
+highest sustained rung per backend: inmemory at 100k msg/s, 1 consumer; kafka at 100k msg/s, 1 consumer; rabbitmq at
+
-highest sustained rung per backend: inmemory at 100k msg/s, 1 consumer; kafka at 100k msg/s, 1 consumer
+5.0k msg/s, 1 consumer; redis at 5.0k msg/s, 1 consumer
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
milliseconds
-
-
-
-
+
+
+
+
+
+
+
+
+
-
-
+
+
+
0.0
-
-
+
+
5.0
-
-
+
+
10
-
-
+
+
15
-
-
+
+
20
+
+
+25
+
+
+
+30
+
+
+
+35
+
+
+
+40
+
+
+
+45
+
-
-
-
-
-
+
+50
+
+
+
+
+
+
+
0.9
-
-
-
-
-
+
+
+
+
+
3.9
-
-
-
-
-
+
+
+
+
+
20
-
-
-
-
-
+
+
+
+
+
8.0
-
-
-
-
-
+
+
+
+
+
13
-
-
-
-
-
+
+
+
+
+
21
-
+
+
+
+
+
+1.3
+
+
+
+
+
+
+15
+
+
+
+
+
+
+47
+
+
+
+
+
+
+1.1
+
+
+
+
+
+
+2.2
+
+
+
+
+
+
+3.1
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/dispatch-latency-1kib.svg b/docs/public/bench/dispatch-latency-1kib.svg
index 1c14fec4..6d1f1232 100644
--- a/docs/public/bench/dispatch-latency-1kib.svg
+++ b/docs/public/bench/dispatch-latency-1kib.svg
@@ -7,102 +7,183 @@ Dispatch latency percentiles
consume_parallel — 1 KiB payload — sustained offered load — lower is better
-
+
dispatch = publish → handler entry, measured while a paced producer held the offered rate and the consumers kept up (a
-
+
sustained offered-load rung); the backlog a corpus-mode row would add is absent by construction
+
+highest sustained rung per backend: inmemory at 100k msg/s, 1 consumer; kafka at 100k msg/s, 1 consumer; rabbitmq at
+
-highest sustained rung per backend: inmemory at 100k msg/s, 1 consumer; kafka at 100k msg/s, 1 consumer
+5.0k msg/s, 1 consumer; redis at 5.0k msg/s, 1 consumer
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
milliseconds
-
-
-
-
+
+
+
+
+
+
+
+
+
-
-
+
+
+
0.0
-
-
+
+
5.0
-
-
+
+
10
-
-
+
+
15
-
-
+
+
20
+
+
+25
+
+
+
+30
+
+
+
+35
+
+
+
+40
+
+
+
+45
+
-
-
-
-
-
+
+50
+
+
+
+
+
+
+
0.9
-
-
-
-
-
+
+
+
+
+
3.9
-
-
-
-
-
+
+
+
+
+
20
-
-
-
-
-
+
+
+
+
+
8.0
-
-
-
-
-
+
+
+
+
+
13
-
-
-
-
-
+
+
+
+
+
21
-
+
+
+
+
+
+1.3
+
+
+
+
+
+
+15
+
+
+
+
+
+
+47
+
+
+
+
+
+
+1.1
+
+
+
+
+
+
+2.2
+
+
+
+
+
+
+3.1
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/dispatch-latency-64kib-dark.svg b/docs/public/bench/dispatch-latency-64kib-dark.svg
index fe5c08c9..48fb7d11 100644
--- a/docs/public/bench/dispatch-latency-64kib-dark.svg
+++ b/docs/public/bench/dispatch-latency-64kib-dark.svg
@@ -7,132 +7,168 @@ Dispatch latency percentiles
consume_parallel — 64 KiB payload — sustained offered load — lower is better
-
+
dispatch = publish → handler entry, measured while a paced producer held the offered rate and the consumers kept up (a
-
+
sustained offered-load rung); the backlog a corpus-mode row would add is absent by construction
+
+highest sustained rung per backend: inmemory at 25k msg/s, 1 consumer; kafka at 5.0k msg/s, 1 consumer; rabbitmq at
+
-highest sustained rung per backend: inmemory at 25k msg/s, 1 consumer; kafka at 5.0k msg/s, 1 consumer
+5.0k msg/s, 2 consumers; redis at 5.0k msg/s, 1 consumer
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
milliseconds
-
-
-
+
+
-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
0.0
-
-
-5.0
-
-
-
+
+
10
-
+
-15
-
-
-
20
-
-
-25
-
-
-
+
+
30
-
-
-35
-
-
-
+
+
40
-
-
-45
-
-
-
+
+
50
-
-
-
-
-
-
+
+
+60
+
+
+
+70
+
+
+
+
+
+
+
0.5
-
-
-
-
-
+
+
+
+
+
13
-
-
-
-
-
+
+
+
+
+
45
-
-
-
-
-
+
+
+
+
+
8.3
-
-
-
-
-
+
+
+
+
+
12
-
-
-
-
-
+
+
+
+
+
18
-
+
+
+
+
+
+2.1
+
+
+
+
+
+
+5.9
+
+
+
+
+
+
+67
+
+
+
+
+
+
+1.4
+
+
+
+
+
+
+2.6
+
+
+
+
+
+
+3.4
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/dispatch-latency-64kib.svg b/docs/public/bench/dispatch-latency-64kib.svg
index 335b35dd..7867e91b 100644
--- a/docs/public/bench/dispatch-latency-64kib.svg
+++ b/docs/public/bench/dispatch-latency-64kib.svg
@@ -7,132 +7,168 @@ Dispatch latency percentiles
consume_parallel — 64 KiB payload — sustained offered load — lower is better
-
+
dispatch = publish → handler entry, measured while a paced producer held the offered rate and the consumers kept up (a
-
+
sustained offered-load rung); the backlog a corpus-mode row would add is absent by construction
+
+highest sustained rung per backend: inmemory at 25k msg/s, 1 consumer; kafka at 5.0k msg/s, 1 consumer; rabbitmq at
+
-highest sustained rung per backend: inmemory at 25k msg/s, 1 consumer; kafka at 5.0k msg/s, 1 consumer
+5.0k msg/s, 2 consumers; redis at 5.0k msg/s, 1 consumer
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
milliseconds
-
-
-
+
+
-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
0.0
-
-
-5.0
-
-
-
+
+
10
-
+
-15
-
-
-
20
-
-
-25
-
-
-
+
+
30
-
-
-35
-
-
-
+
+
40
-
-
-45
-
-
-
+
+
50
-
-
-
-
-
-
+
+
+60
+
+
+
+70
+
+
+
+
+
+
+
0.5
-
-
-
-
-
+
+
+
+
+
13
-
-
-
-
-
+
+
+
+
+
45
-
-
-
-
-
+
+
+
+
+
8.3
-
-
-
-
-
+
+
+
+
+
12
-
-
-
-
-
+
+
+
+
+
18
-
+
+
+
+
+
+2.1
+
+
+
+
+
+
+5.9
+
+
+
+
+
+
+67
+
+
+
+
+
+
+1.4
+
+
+
+
+
+
+2.6
+
+
+
+
+
+
+3.4
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/dispatch-latency-dark.svg b/docs/public/bench/dispatch-latency-dark.svg
index a65809f6..b3299322 100644
--- a/docs/public/bench/dispatch-latency-dark.svg
+++ b/docs/public/bench/dispatch-latency-dark.svg
@@ -7,107 +7,158 @@ Dispatch latency percentiles
consume_parallel — 64 B payload — sustained offered load — lower is better
-
+
dispatch = publish → handler entry, measured while a paced producer held the offered rate and the consumers kept up (a
-
+
sustained offered-load rung); the backlog a corpus-mode row would add is absent by construction
+
+highest sustained rung per backend: inmemory at 100k msg/s, 1 consumer; kafka at 100k msg/s, 1 consumer; rabbitmq at
+
-highest sustained rung per backend: inmemory at 100k msg/s, 1 consumer; kafka at 100k msg/s, 1 consumer
+25k msg/s, 1 consumer; redis at 5.0k msg/s, 1 consumer
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
milliseconds
-
-
-
-
-
+
+
+
+
+
-
-
+
+
0.0
-
-
+
+
5.0
-
-
+
+
10
-
-
+
+
15
-
-
+
+
20
-
+
25
-
-
-
-
-
+
+
+
+
+
0.9
-
-
-
-
-
+
+
+
+
+
3.5
-
-
-
-
-
+
+
+
+
+
7.1
-
-
-
-
-
+
+
+
+
+
8.2
-
-
-
-
-
+
+
+
+
+
13
-
-
-
-
-
+
+
+
+
+
22
-
+
+
+
+
+
+2.7
+
+
+
+
+
+
+6.5
+
+
+
+
+
+
+14
+
+
+
+
+
+
+1.1
+
+
+
+
+
+
+2.3
+
+
+
+
+
+
+4.3
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/dispatch-latency.svg b/docs/public/bench/dispatch-latency.svg
index 6a3c052c..2e62c22e 100644
--- a/docs/public/bench/dispatch-latency.svg
+++ b/docs/public/bench/dispatch-latency.svg
@@ -7,107 +7,158 @@ Dispatch latency percentiles
consume_parallel — 64 B payload — sustained offered load — lower is better
-
+
dispatch = publish → handler entry, measured while a paced producer held the offered rate and the consumers kept up (a
-
+
sustained offered-load rung); the backlog a corpus-mode row would add is absent by construction
+
+highest sustained rung per backend: inmemory at 100k msg/s, 1 consumer; kafka at 100k msg/s, 1 consumer; rabbitmq at
+
-highest sustained rung per backend: inmemory at 100k msg/s, 1 consumer; kafka at 100k msg/s, 1 consumer
+25k msg/s, 1 consumer; redis at 5.0k msg/s, 1 consumer
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
milliseconds
-
-
-
-
-
+
+
+
+
+
-
-
+
+
0.0
-
-
+
+
5.0
-
-
+
+
10
-
-
+
+
15
-
-
+
+
20
-
+
25
-
-
-
-
-
+
+
+
+
+
0.9
-
-
-
-
-
+
+
+
+
+
3.5
-
-
-
-
-
+
+
+
+
+
7.1
-
-
-
-
-
+
+
+
+
+
8.2
-
-
-
-
-
+
+
+
+
+
13
-
-
-
-
-
+
+
+
+
+
22
-
+
+
+
+
+
+2.7
+
+
+
+
+
+
+6.5
+
+
+
+
+
+
+14
+
+
+
+
+
+
+1.1
+
+
+
+
+
+
+2.3
+
+
+
+
+
+
+4.3
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/framework-overhead-dark.svg b/docs/public/bench/framework-overhead-dark.svg
index 92d2dcde..a6c926a0 100644
--- a/docs/public/bench/framework-overhead-dark.svg
+++ b/docs/public/bench/framework-overhead-dark.svg
@@ -35,13 +35,13 @@ from the moment every worker was assigned until 90 % of a corpus of 6.0M message
been consumed; no producer ran in the window
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
nanoseconds / message
diff --git a/docs/public/bench/framework-overhead.svg b/docs/public/bench/framework-overhead.svg
index e72cf108..4d49c260 100644
--- a/docs/public/bench/framework-overhead.svg
+++ b/docs/public/bench/framework-overhead.svg
@@ -35,13 +35,13 @@ from the moment every worker was assigned until 90 % of a corpus of 6.0M message
been consumed; no producer ran in the window
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
nanoseconds / message
diff --git a/docs/public/bench/parallel-vs-sequenced-1kib-dark.svg b/docs/public/bench/parallel-vs-sequenced-1kib-dark.svg
index 5acca4ad..c5ccb177 100644
--- a/docs/public/bench/parallel-vs-sequenced-1kib-dark.svg
+++ b/docs/public/bench/parallel-vs-sequenced-1kib-dark.svg
@@ -7,121 +7,174 @@ Parallel vs sequenced consume
1 KiB payload — least-parallel measurement per mode — what ordering costs — higher is better
+
+redis / sequenced (fifo): failed to run — absent, not zero; see failures[] in the results document
+
+
+kafka, rabbitmq / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain, so the
+
+
+true rate is at least the bar shown
+
+
+rabbitmq / parallel, sequenced (fifo), batch: measured at 8 workers (the least-parallel count the measured modes
+
-kafka / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain, so the true rate is
+share)
-at least the bar shown
+inmemory / sequenced (fifo): measured, but every window under 1 s — too short to publish as a rate, even a lower bound
-inmemory / sequenced (fifo): measured, but every window under 1 s — too short to publish as a rate, even a lower bound
+batch bars: up to 500 messages or 250 ms per batch
-batch bars: up to 500 messages or 250 ms per batch
+drain (inmemory, kafka, rabbitmq, redis): each consume_batch / consume_parallel point is the processing rate of the
-drain (inmemory, kafka): each consume_batch / consume_parallel point is the processing rate of the consumers from the
+consumers from the moment every worker was assigned until 90 % of a corpus of 3.1M messages, published before they
-moment every worker was assigned until 90 % of a corpus of 3.1M messages, published before they started, had been
+started, had been consumed; no producer ran in the window
-consumed; no producer ran in the window
+redis: 1 cell in this slice failed to run — absent, not zero; see failures[]
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
messages / second
-
-
-
+
+
-
-
-
-
-
-
+
+
+
+
+
+
+
0.0
-
-
+
+
200k
-
-
+
+
400k
-
-
+
+
600k
-
-
+
+
800k
-
-
+
+
1.0M
-
-
+
+
1.2M
-
-
+
+
1.4M
-
-
-
-
-
-
+
+
+
+
+
+
637k
-
+
n/s
-
-
-
-
-
+
+
+
+
+
1.3M
-
-
-
-
-
+
+
+
+
+
81k
-
+
≥1.6k
-
-
-
-
-
+
+
+
+
+
86k
-
+
+
+
+
+
+28k
+
+
+
+≥10.0k
+
+
+
+
+
+
+30k
+
+
+
+
+
+
+11k
+
+
+n/s
+
+
+
+
+
+
+99k
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/parallel-vs-sequenced-1kib.svg b/docs/public/bench/parallel-vs-sequenced-1kib.svg
index bf67e337..1ef97f24 100644
--- a/docs/public/bench/parallel-vs-sequenced-1kib.svg
+++ b/docs/public/bench/parallel-vs-sequenced-1kib.svg
@@ -7,121 +7,174 @@ Parallel vs sequenced consume
1 KiB payload — least-parallel measurement per mode — what ordering costs — higher is better
+
+redis / sequenced (fifo): failed to run — absent, not zero; see failures[] in the results document
+
+
+kafka, rabbitmq / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain, so the
+
+
+true rate is at least the bar shown
+
+
+rabbitmq / parallel, sequenced (fifo), batch: measured at 8 workers (the least-parallel count the measured modes
+
-kafka / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain, so the true rate is
+share)
-at least the bar shown
+inmemory / sequenced (fifo): measured, but every window under 1 s — too short to publish as a rate, even a lower bound
-inmemory / sequenced (fifo): measured, but every window under 1 s — too short to publish as a rate, even a lower bound
+batch bars: up to 500 messages or 250 ms per batch
-batch bars: up to 500 messages or 250 ms per batch
+drain (inmemory, kafka, rabbitmq, redis): each consume_batch / consume_parallel point is the processing rate of the
-drain (inmemory, kafka): each consume_batch / consume_parallel point is the processing rate of the consumers from the
+consumers from the moment every worker was assigned until 90 % of a corpus of 3.1M messages, published before they
-moment every worker was assigned until 90 % of a corpus of 3.1M messages, published before they started, had been
+started, had been consumed; no producer ran in the window
-consumed; no producer ran in the window
+redis: 1 cell in this slice failed to run — absent, not zero; see failures[]
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
messages / second
-
-
-
+
+
-
-
-
-
-
-
+
+
+
+
+
+
+
0.0
-
-
+
+
200k
-
-
+
+
400k
-
-
+
+
600k
-
-
+
+
800k
-
-
+
+
1.0M
-
-
+
+
1.2M
-
-
+
+
1.4M
-
-
-
-
-
-
+
+
+
+
+
+
637k
-
+
n/s
-
-
-
-
-
+
+
+
+
+
1.3M
-
-
-
-
-
+
+
+
+
+
81k
-
+
≥1.6k
-
-
-
-
-
+
+
+
+
+
86k
-
+
+
+
+
+
+28k
+
+
+
+≥10.0k
+
+
+
+
+
+
+30k
+
+
+
+
+
+
+11k
+
+
+n/s
+
+
+
+
+
+
+99k
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/parallel-vs-sequenced-64kib-dark.svg b/docs/public/bench/parallel-vs-sequenced-64kib-dark.svg
index bbd967a1..2419d7b2 100644
--- a/docs/public/bench/parallel-vs-sequenced-64kib-dark.svg
+++ b/docs/public/bench/parallel-vs-sequenced-64kib-dark.svg
@@ -7,143 +7,199 @@ Parallel vs sequenced consume
64 KiB payload — least-parallel measurement per mode — what ordering costs — higher is better
+
+redis / sequenced (fifo): failed to run — absent, not zero; see failures[] in the results document
+
+
+inmemory, kafka, rabbitmq / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain,
+
+
+so the true rate is at least the bar shown
+
+
+kafka / parallel: measured at 2 workers (no worker count is shared by the measured modes, so the bars are not directly
+
-inmemory, kafka / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain, so the
+comparable)
-true rate is at least the bar shown
+rabbitmq / sequenced (fifo): measured at 8 workers (no worker count is shared by the measured modes, so the bars are
-kafka / parallel: measured at 2 workers (no worker count is shared by the measured modes, so the bars are not directly
+not directly comparable)
-comparable)
+inmemory / sequenced (fifo): measured at 8 workers (the least-parallel count the measured modes share)
-inmemory / sequenced (fifo): measured at 8 workers (the least-parallel count the measured modes share)
+inmemory / parallel, batch: measured, but every window under 1 s — too short to publish as a rate, even a lower bound
-inmemory / parallel, batch: measured, but every window under 1 s — too short to publish as a rate, even a lower bound
+batch bars: up to 500 messages or 250 ms per batch
-batch bars: up to 500 messages or 250 ms per batch
+drain (inmemory, kafka, rabbitmq, redis): each consume_batch / consume_parallel point is the processing rate of the
-drain (inmemory, kafka): each consume_batch / consume_parallel point is the processing rate of the consumers from the
+consumers from the moment every worker was assigned until 90 % of a corpus of 49k messages, published before they
-moment every worker was assigned until 90 % of a corpus of 49k messages, published before they started, had been
+started, had been consumed; no producer ran in the window
-consumed; no producer ran in the window
+inmemory: 1 cell in this slice failed to run — absent, not zero; see failures[]
-inmemory: 1 cell in this slice failed to run — absent, not zero; see failures[]
+rabbitmq, redis: 2 cells in this slice failed to run — absent, not zero; see failures[]
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
messages / second
-
-
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+
0.0
-
-
+
+
5.0k
-
-
+
+
10k
-
-
+
+
15k
-
-
+
+
20k
-
-
+
+
25k
-
-
+
+
30k
-
-
+
+
35k
-
-
+
+
40k
-
-
+
+
45k
-
-
+
+
n/s
-
-
-
-
-
+
+
+
+
+
≥30k
-
+
n/s
-
-
-
-
-
+
+
+
+
+
41k
-
-
-
-
-
+
+
+
+
+
≥1.5k
-
-
-
-
-
+
+
+
+
+
30k
-
+
+
+
+
+
+1.4k
+
+
+
+
+
+
+≥3.2k
+
+
+
+
+
+
+4.3k
+
+
+
+
+
+
+7.1k
+
+
+n/s
+
+
+
+
+
+
+17k
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/parallel-vs-sequenced-64kib.svg b/docs/public/bench/parallel-vs-sequenced-64kib.svg
index bf98fd50..172ba4bd 100644
--- a/docs/public/bench/parallel-vs-sequenced-64kib.svg
+++ b/docs/public/bench/parallel-vs-sequenced-64kib.svg
@@ -7,143 +7,199 @@ Parallel vs sequenced consume
64 KiB payload — least-parallel measurement per mode — what ordering costs — higher is better
+
+redis / sequenced (fifo): failed to run — absent, not zero; see failures[] in the results document
+
+
+inmemory, kafka, rabbitmq / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain,
+
+
+so the true rate is at least the bar shown
+
+
+kafka / parallel: measured at 2 workers (no worker count is shared by the measured modes, so the bars are not directly
+
-inmemory, kafka / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain, so the
+comparable)
-true rate is at least the bar shown
+rabbitmq / sequenced (fifo): measured at 8 workers (no worker count is shared by the measured modes, so the bars are
-kafka / parallel: measured at 2 workers (no worker count is shared by the measured modes, so the bars are not directly
+not directly comparable)
-comparable)
+inmemory / sequenced (fifo): measured at 8 workers (the least-parallel count the measured modes share)
-inmemory / sequenced (fifo): measured at 8 workers (the least-parallel count the measured modes share)
+inmemory / parallel, batch: measured, but every window under 1 s — too short to publish as a rate, even a lower bound
-inmemory / parallel, batch: measured, but every window under 1 s — too short to publish as a rate, even a lower bound
+batch bars: up to 500 messages or 250 ms per batch
-batch bars: up to 500 messages or 250 ms per batch
+drain (inmemory, kafka, rabbitmq, redis): each consume_batch / consume_parallel point is the processing rate of the
-drain (inmemory, kafka): each consume_batch / consume_parallel point is the processing rate of the consumers from the
+consumers from the moment every worker was assigned until 90 % of a corpus of 49k messages, published before they
-moment every worker was assigned until 90 % of a corpus of 49k messages, published before they started, had been
+started, had been consumed; no producer ran in the window
-consumed; no producer ran in the window
+inmemory: 1 cell in this slice failed to run — absent, not zero; see failures[]
-inmemory: 1 cell in this slice failed to run — absent, not zero; see failures[]
+rabbitmq, redis: 2 cells in this slice failed to run — absent, not zero; see failures[]
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
messages / second
-
-
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+
0.0
-
-
+
+
5.0k
-
-
+
+
10k
-
-
+
+
15k
-
-
+
+
20k
-
-
+
+
25k
-
-
+
+
30k
-
-
+
+
35k
-
-
+
+
40k
-
-
+
+
45k
-
-
+
+
n/s
-
-
-
-
-
+
+
+
+
+
≥30k
-
+
n/s
-
-
-
-
-
+
+
+
+
+
41k
-
-
-
-
-
+
+
+
+
+
≥1.5k
-
-
-
-
-
+
+
+
+
+
30k
-
+
+
+
+
+
+1.4k
+
+
+
+
+
+
+≥3.2k
+
+
+
+
+
+
+4.3k
+
+
+
+
+
+
+7.1k
+
+
+n/s
+
+
+
+
+
+
+17k
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/parallel-vs-sequenced-dark.svg b/docs/public/bench/parallel-vs-sequenced-dark.svg
index a54c5e37..fde9c02b 100644
--- a/docs/public/bench/parallel-vs-sequenced-dark.svg
+++ b/docs/public/bench/parallel-vs-sequenced-dark.svg
@@ -7,111 +7,163 @@ Parallel vs sequenced consume
64 B payload — least-parallel measurement per mode — what ordering costs — higher is better
+
+redis / sequenced (fifo): failed to run — absent, not zero; see failures[] in the results document
+
+
+kafka, rabbitmq / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain, so the
+
+
+true rate is at least the bar shown
+
+
+redis / parallel, batch: measured at 2 workers (the least-parallel count the measured modes share)
+
+
+rabbitmq / parallel, sequenced (fifo), batch: measured at 8 workers (the least-parallel count the measured modes
+
-kafka / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain, so the true rate is
+share)
-at least the bar shown
+inmemory / sequenced (fifo): measured, but every window under 1 s — too short to publish as a rate, even a lower bound
-inmemory / sequenced (fifo): measured, but every window under 1 s — too short to publish as a rate, even a lower bound
+batch bars: up to 500 messages or 250 ms per batch
-batch bars: up to 500 messages or 250 ms per batch
+drain (inmemory, kafka, rabbitmq, redis): each consume_batch / consume_parallel point is the processing rate of the
-drain (inmemory, kafka): each consume_batch / consume_parallel point is the processing rate of the consumers from the
+consumers from the moment every worker was assigned until 90 % of a corpus of 6.0M messages, published before they
-moment every worker was assigned until 90 % of a corpus of 6.0M messages, published before they started, had been
+started, had been consumed; no producer ran in the window
-consumed; no producer ran in the window
+redis: 2 cells in this slice failed to run — absent, not zero; see failures[]
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
messages / second
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
0.0
-
-
+
+
500k
-
-
+
+
1.0M
-
-
+
+
1.5M
-
-
+
+
2.0M
-
-
+
+
2.5M
-
-
-
-
-
-
+
+
+
+
+
+
654k
-
+
n/s
-
-
-
-
-
+
+
+
+
+
2.5M
-
-
-
-
-
+
+
+
+
+
114k
-
+
≥1.6k
-
-
-
-
-
+
+
+
+
+
112k
-
+
+
+
+
+
+26k
+
+
+≥2.4k
+
+
+
+
+
+
+33k
+
+
+
+20k
+
+
+n/s
+
+
+
+
+
+
+311k
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/parallel-vs-sequenced.svg b/docs/public/bench/parallel-vs-sequenced.svg
index ecde6fe8..98e70af1 100644
--- a/docs/public/bench/parallel-vs-sequenced.svg
+++ b/docs/public/bench/parallel-vs-sequenced.svg
@@ -7,111 +7,163 @@ Parallel vs sequenced consume
64 B payload — least-parallel measurement per mode — what ordering costs — higher is better
+
+redis / sequenced (fifo): failed to run — absent, not zero; see failures[] in the results document
+
+
+kafka, rabbitmq / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain, so the
+
+
+true rate is at least the bar shown
+
+
+redis / parallel, batch: measured at 2 workers (the least-parallel count the measured modes share)
+
+
+rabbitmq / parallel, sequenced (fifo), batch: measured at 8 workers (the least-parallel count the measured modes
+
-kafka / sequenced (fifo): lower bound (muted bar) — this window cannot separate setup from drain, so the true rate is
+share)
-at least the bar shown
+inmemory / sequenced (fifo): measured, but every window under 1 s — too short to publish as a rate, even a lower bound
-inmemory / sequenced (fifo): measured, but every window under 1 s — too short to publish as a rate, even a lower bound
+batch bars: up to 500 messages or 250 ms per batch
-batch bars: up to 500 messages or 250 ms per batch
+drain (inmemory, kafka, rabbitmq, redis): each consume_batch / consume_parallel point is the processing rate of the
-drain (inmemory, kafka): each consume_batch / consume_parallel point is the processing rate of the consumers from the
+consumers from the moment every worker was assigned until 90 % of a corpus of 6.0M messages, published before they
-moment every worker was assigned until 90 % of a corpus of 6.0M messages, published before they started, had been
+started, had been consumed; no producer ran in the window
-consumed; no producer ran in the window
+redis: 2 cells in this slice failed to run — absent, not zero; see failures[]
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
messages / second
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
0.0
-
-
+
+
500k
-
-
+
+
1.0M
-
-
+
+
1.5M
-
-
+
+
2.0M
-
-
+
+
2.5M
-
-
-
-
-
-
+
+
+
+
+
+
654k
-
+
n/s
-
-
-
-
-
+
+
+
+
+
2.5M
-
-
-
-
-
+
+
+
+
+
114k
-
+
≥1.6k
-
-
-
-
-
+
+
+
+
+
112k
-
+
+
+
+
+
+26k
+
+
+≥2.4k
+
+
+
+
+
+
+33k
+
+
+
+20k
+
+
+n/s
+
+
+
+
+
+
+311k
+
+
inmemory
-
+
kafka
-
+
+rabbitmq
+
+
+redis
+
+
backend
diff --git a/docs/public/bench/throughput-vs-consumers-1kib-dark.svg b/docs/public/bench/throughput-vs-consumers-1kib-dark.svg
index 1611abc1..270fb48a 100644
--- a/docs/public/bench/throughput-vs-consumers-1kib-dark.svg
+++ b/docs/public/bench/throughput-vs-consumers-1kib-dark.svg
@@ -8,22 +8,22 @@ Throughput vs consumer count
consume_parallel — 1 KiB payload — higher is better
-drain (inmemory, kafka): each consume_parallel point is the processing rate of the consumers from the moment every
+drain (inmemory, kafka, rabbitmq, redis): each consume_parallel point is the processing rate of the consumers from the
-worker was assigned until 90 % of a corpus of 3.1M messages, published before they started, had been consumed; no
+moment every worker was assigned until 90 % of a corpus of 3.1M messages, published before they started, had been
-producer ran in the window
+consumed; no producer ran in the window
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
messages / second — log scale
@@ -126,6 +126,8 @@ messages / second — log scale
+
+
@@ -142,6 +144,22 @@ messages / second — log scale
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
kafka
@@ -150,6 +168,14 @@ kafka
inmemory
+
+
+redis
+
+
+
+rabbitmq
+
1
@@ -173,4 +199,12 @@ inmemory
kafka
+
+
+rabbitmq
+
+
+
+redis
+
diff --git a/docs/public/bench/throughput-vs-consumers-1kib.svg b/docs/public/bench/throughput-vs-consumers-1kib.svg
index 6ef27988..584654a0 100644
--- a/docs/public/bench/throughput-vs-consumers-1kib.svg
+++ b/docs/public/bench/throughput-vs-consumers-1kib.svg
@@ -8,22 +8,22 @@ Throughput vs consumer count
consume_parallel — 1 KiB payload — higher is better
-drain (inmemory, kafka): each consume_parallel point is the processing rate of the consumers from the moment every
+drain (inmemory, kafka, rabbitmq, redis): each consume_parallel point is the processing rate of the consumers from the
-worker was assigned until 90 % of a corpus of 3.1M messages, published before they started, had been consumed; no
+moment every worker was assigned until 90 % of a corpus of 3.1M messages, published before they started, had been
-producer ran in the window
+consumed; no producer ran in the window
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
messages / second — log scale
@@ -126,6 +126,8 @@ messages / second — log scale
+
+
@@ -142,6 +144,22 @@ messages / second — log scale
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
kafka
@@ -150,6 +168,14 @@ kafka
inmemory
+
+
+redis
+
+
+
+rabbitmq
+
1
@@ -173,4 +199,12 @@ inmemory
kafka
+
+
+rabbitmq
+
+
+
+redis
+
diff --git a/docs/public/bench/throughput-vs-consumers-64kib-dark.svg b/docs/public/bench/throughput-vs-consumers-64kib-dark.svg
index f98354f4..c2a82c38 100644
--- a/docs/public/bench/throughput-vs-consumers-64kib-dark.svg
+++ b/docs/public/bench/throughput-vs-consumers-64kib-dark.svg
@@ -7,76 +7,158 @@ Throughput vs consumer count
consume_parallel — 64 KiB payload — higher is better
-
+
inmemory: measured, but no drain rate is published for this slice — window under 1 s, too short to publish as a rate
-
+
at consumers 1, 2, 4, 8
-
+
kafka: partial — not plotted: window under 1 s, too short to publish as a rate at consumers 1, 4, 8
+
+rabbitmq: partial — not plotted: failed to run — absent, not zero; see failures[] in the results document (a failed
+
+
+drain; the cell's ladder rungs are not its ceiling) at consumers 8
+
+
+drain (inmemory, kafka, rabbitmq, redis): each consume_parallel point is the processing rate of the consumers from the
+
-drain (inmemory, kafka): each consume_parallel point is the processing rate of the consumers from the moment every
+moment every worker was assigned until 90 % of a corpus of 49k messages, published before they started, had been
-worker was assigned until 90 % of a corpus of 49k messages, published before they started, had been consumed; no
+consumed; no producer ran in the window
-producer ran in the window
+rabbitmq, redis: 1 cell in this slice failed to run — absent, not zero; see failures[]
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
messages / second — log scale
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+1.0k
+
+
+
+2.0k
+
+
+
+3.0k
+
+
+
+4.0k
+
+
+
+5.0k
+
+
+
+6.0k
+
+
+
+7.0k
+
+
+
+8.0k
+
+
+
+9.0k
+
+
+
+10k
+
+
+
10k
-
-
+
+
20k
-
-
+
+
30k
-
-
+
+
40k
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
kafka
-
+
+rabbitmq
+
+
+
+redis
+
+
1
-
+
2
-
+
4
-
+
8
-
+
consumers
@@ -87,4 +169,12 @@ inmemory (withheld)
kafka (single point)
+
+
+rabbitmq
+
+
+
+redis
+
diff --git a/docs/public/bench/throughput-vs-consumers-64kib.svg b/docs/public/bench/throughput-vs-consumers-64kib.svg
index e4e9d0fd..604745ff 100644
--- a/docs/public/bench/throughput-vs-consumers-64kib.svg
+++ b/docs/public/bench/throughput-vs-consumers-64kib.svg
@@ -7,76 +7,158 @@ Throughput vs consumer count
consume_parallel — 64 KiB payload — higher is better
-
+
inmemory: measured, but no drain rate is published for this slice — window under 1 s, too short to publish as a rate
-
+
at consumers 1, 2, 4, 8
-
+
kafka: partial — not plotted: window under 1 s, too short to publish as a rate at consumers 1, 4, 8
+
+rabbitmq: partial — not plotted: failed to run — absent, not zero; see failures[] in the results document (a failed
+
+
+drain; the cell's ladder rungs are not its ceiling) at consumers 8
+
+
+drain (inmemory, kafka, rabbitmq, redis): each consume_parallel point is the processing rate of the consumers from the
+
-drain (inmemory, kafka): each consume_parallel point is the processing rate of the consumers from the moment every
+moment every worker was assigned until 90 % of a corpus of 49k messages, published before they started, had been
-worker was assigned until 90 % of a corpus of 49k messages, published before they started, had been consumed; no
+consumed; no producer ran in the window
-producer ran in the window
+rabbitmq, redis: 1 cell in this slice failed to run — absent, not zero; see failures[]
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
-
+
messages / second — log scale
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+1.0k
+
+
+
+2.0k
+
+
+
+3.0k
+
+
+
+4.0k
+
+
+
+5.0k
+
+
+
+6.0k
+
+
+
+7.0k
+
+
+
+8.0k
+
+
+
+9.0k
+
+
+
+10k
+
+
+
10k
-
-
+
+
20k
-
-
+
+
30k
-
-
+
+
40k
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
kafka
-
+
+rabbitmq
+
+
+
+redis
+
+
1
-
+
2
-
+
4
-
+
8
-
+
consumers
@@ -87,4 +169,12 @@ inmemory (withheld)
kafka (single point)
+
+
+rabbitmq
+
+
+
+redis
+
diff --git a/docs/public/bench/throughput-vs-consumers-dark.svg b/docs/public/bench/throughput-vs-consumers-dark.svg
index fd175c08..f91d6008 100644
--- a/docs/public/bench/throughput-vs-consumers-dark.svg
+++ b/docs/public/bench/throughput-vs-consumers-dark.svg
@@ -8,98 +8,174 @@ Throughput vs consumer count
consume_parallel — 64 B payload — higher is better
-drain (inmemory, kafka): each consume_parallel point is the processing rate of the consumers from the moment every
+drain (inmemory, kafka, rabbitmq, redis): each consume_parallel point is the processing rate of the consumers from the
-worker was assigned until 90 % of a corpus of 6.0M messages, published before they started, had been consumed; no
+moment every worker was assigned until 90 % of a corpus of 6.0M messages, published before they started, had been
-producer ran in the window
+consumed; no producer ran in the window
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
messages / second — log scale
-
+
+
+
+
+
+
+
-
-
-
+
+
+
+
+
-
-
+
+
+
+
-100k
+10k
-
-200k
+
+20k
+
+
+
+30k
+
+
+
+40k
+
+
+
+50k
+
+
+
+60k
+
+
+
+70k
-
+
+
+80k
+
+
-300k
+90k
-
+
+100k
+
+
+
+100k
+
+
+
+200k
+
+
+
+300k
+
+
+
400k
-
-
+
+
500k
-
-
+
+
600k
-
-
+
+
700k
-
-
+
+
800k
-
-
+
+
900k
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
kafka
-
-
+
+
inmemory
+
+
+rabbitmq
+
+
+
+redis
+
1
@@ -123,4 +199,12 @@ inmemory
kafka
+
+
+rabbitmq
+
+
+
+redis
+
diff --git a/docs/public/bench/throughput-vs-consumers.svg b/docs/public/bench/throughput-vs-consumers.svg
index 3dd6883e..7d461deb 100644
--- a/docs/public/bench/throughput-vs-consumers.svg
+++ b/docs/public/bench/throughput-vs-consumers.svg
@@ -8,98 +8,174 @@ Throughput vs consumer count
consume_parallel — 64 B payload — higher is better
-drain (inmemory, kafka): each consume_parallel point is the processing rate of the consumers from the moment every
+drain (inmemory, kafka, rabbitmq, redis): each consume_parallel point is the processing rate of the consumers from the
-worker was assigned until 90 % of a corpus of 6.0M messages, published before they started, had been consumed; no
+moment every worker was assigned until 90 % of a corpus of 6.0M messages, published before they started, had been
-producer ran in the window
+consumed; no producer ran in the window
-Generated 2026-09-04T13:16:16Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
+Generated 2026-09-07T13:47:38Z — shove 0.14.0 — Apple M4 Max (16c / 64 GB)
Apple M4 Max — 16 cores — 64 GB RAM — macOS 26.6.2 — rustc 1.91.1 (ed61e7d7e 2025-11-07) — handler: zero (no-op)
-1 recorded failure(s) in the dataset — see failures[]
+9 recorded failure(s) in the dataset — see failures[]
messages / second — log scale
-
+
+
+
+
+
+
+
-
-
-
+
+
+
+
+
-
-
+
+
+
+
-100k
+10k
-
-200k
+
+20k
+
+
+
+30k
+
+
+
+40k
+
+
+
+50k
+
+
+
+60k
+
+
+
+70k
-
+
+
+80k
+
+
-300k
+90k
-
+
+100k
+
+
+
+100k
+
+
+
+200k
+
+
+
+300k
+
+
+
400k
-
-
+
+
500k
-
-
+
+
600k
-
-
+
+
700k
-
-
+