History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"axonometric"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 540 | 2025-12-28 09:02:53 | axonometric | 1 | 49908 | 1 | 0.830 | 60130.1 |
| 539 | 2025-12-12 04:20:55 | axonometric | 1 | 49908 | 1 | 4.046 | 12335.1 |
| 538 | 2025-12-08 19:44:49 | axonometric | 1 | 49908 | 1 | 0.830 | 60130.1 |
| 537 | 2025-11-12 03:16:18 | axonometric | 1 | 49908 | 1 | 0.813 | 61387.5 |
| 536 | 2025-10-20 07:59:26 | axonometric | 1 | 49908 | 1 | 7.796 | 6401.7 |
| 535 | 2025-10-20 07:59:19 | axonometric | 1 | 49908 | 1 | 4.966 | 10049.9 |
| 534 | 2025-10-20 07:59:02 | axonometric | 1 | 49908 | 1 | 2.110 | 23653.1 |
| 533 | 2025-10-20 07:58:47 | axonometric | 1 | 49908 | 1 | 3.550 | 14058.6 |
| 532 | 2025-08-15 09:04:58 | axonometric | 2 | 86808 | 2 | 5.280 | 16440.9 |
| 531 | 2025-08-14 01:44:44 | axonometric | 1 | 49908 | 1 | 0.720 | 69316.7 |
| 530 | 2025-08-05 01:27:10 | axonometric | 1 | 49908 | 1 | 2.030 | 24585.2 |
| 529 | 2025-07-30 03:53:15 | axonometric | 2 | 86808 | 2 | 5.236 | 16579.1 |
| 528 | 2025-07-25 20:15:57 | axonometric | 1 | 49908 | 1 | 1.140 | 43778.9 |
| 527 | 2025-07-09 22:48:58 | axonometric | 1 | 49908 | 1 | 6.203 | 8045.8 |
| 526 | 2025-07-09 03:41:52 | axonometric | 4 | 148819 | 56 | 41.080 | 3622.7 |
| 525 | 2025-07-05 11:51:44 | axonometric | 4 | 148819 | 56 | 66.283 | 2245.2 |
| 524 | 2025-06-17 01:29:21 | axonometric | 4 | 148819 | 56 | 44.610 | 3336.0 |
| 523 | 2025-06-15 00:03:25 | axonometric | 4 | 148819 | 56 | 13.080 | 11377.6 |
| 522 | 2025-06-03 22:12:16 | axonometric | 1 | 49908 | 1 | 3.846 | 12976.6 |
| 521 | 2025-06-03 02:20:10 | axonometric | 3 | 121633 | 15 | 5.266 | 23097.8 |
| 520 | 2025-06-03 01:15:36 | axonometric | 4 | 148819 | 56 | 8.330 | 17865.4 |
| 519 | 2025-05-29 00:21:51 | axonometric | 1 | 49908 | 1 | 2.093 | 23845.2 |
| 518 | 2025-05-28 14:14:21 | axonometric | 2 | 86808 | 2 | 3.890 | 22315.7 |
| 517 | 2025-05-28 10:33:16 | axonometric | 3 | 121633 | 15 | 5.486 | 22171.5 |
| 516 | 2025-05-20 15:54:22 | axonometric | 1 | 49908 | 1 | 2.266 | 22024.7 |
| 515 | 2025-05-10 10:54:19 | axonometric | 1 | 49908 | 1 | 3.766 | 13252.3 |
| 514 | 2025-05-03 22:03:34 | axonometric | 1 | 49908 | 1 | 2.516 | 19836.2 |
| 513 | 2025-05-03 04:22:24 | axonometric | 3 | 121633 | 15 | 26.080 | 4663.8 |
| 512 | 2025-04-30 04:25:05 | axonometric | 3 | 121633 | 15 | 31.350 | 3879.8 |
| 511 | 2025-04-28 04:52:23 | axonometric | 1 | 49908 | 1 | 1.796 | 27788.4 |
| 510 | 2025-04-23 03:26:59 | axonometric | 3 | 121633 | 15 | 30.580 | 3977.5 |
| 509 | 2025-04-08 09:09:20 | axonometric | 3 | 121633 | 15 | 21.156 | 5749.3 |
| 508 | 2025-04-06 15:04:36 | axonometric | 1 | 49908 | 1 | 3.173 | 15729.0 |
| 507 | 2025-04-06 04:43:21 | axonometric | 2 | 86808 | 2 | 11.563 | 7507.4 |
| 506 | 2025-04-06 04:42:21 | axonometric | 3 | 121633 | 15 | 23.970 | 5074.4 |
| 505 | 2025-04-05 01:38:06 | axonometric | 4 | 148819 | 56 | 40.766 | 3650.6 |
| 504 | 2025-04-04 04:37:24 | axonometric | 4 | 148819 | 56 | 55.050 | 2703.3 |
| 503 | 2025-03-28 05:26:30 | axonometric | 4 | 148819 | 56 | 47.376 | 3141.2 |
| 502 | 2025-03-25 22:59:02 | axonometric | 1 | 49908 | 1 | 4.016 | 12427.3 |
| 501 | 2025-03-25 22:21:46 | axonometric | 1 | 49908 | 1 | 3.780 | 13203.2 |
| 500 | 2025-03-25 00:45:52 | axonometric | 1 | 49908 | 1 | 4.060 | 12292.6 |
| 499 | 2025-03-20 05:53:07 | axonometric | 1 | 49908 | 1 | 4.326 | 11536.8 |
| 498 | 2025-03-17 06:12:24 | axonometric | 4 | 148819 | 56 | 47.986 | 3101.3 |
| 497 | 2025-03-07 06:37:09 | axonometric | 4 | 148819 | 56 | 48.756 | 3052.3 |
| 496 | 2025-03-02 16:51:09 | axonometric | 1 | 49908 | 1 | 2.000 | 24954.0 |
| 495 | 2025-02-23 20:39:42 | axonometric | 4 | 148819 | 56 | 35.686 | 4170.2 |
| 494 | 2025-02-22 22:22:34 | axonometric | 4 | 148819 | 56 | 47.846 | 3110.4 |
| 493 | 2025-02-21 12:47:14 | axonometric | 3 | 121633 | 15 | 27.643 | 4400.1 |
| 492 | 2025-02-21 12:46:55 | axonometric | 4 | 148819 | 56 | 33.283 | 4471.3 |
| 491 | 2025-02-21 12:47:07 | axonometric | 2 | 86808 | 2 | 11.610 | 7477.0 |
| 490 | 2025-02-21 12:45:12 | axonometric | 1 | 49908 | 1 | 4.016 | 12427.3 |
| 489 | 2025-02-07 01:22:53 | axonometric | 1 | 49908 | 1 | 3.500 | 14259.4 |
| 488 | 2025-02-03 03:29:53 | axonometric | 2 | 86808 | 2 | 14.173 | 6124.9 |
| 487 | 2025-01-29 21:30:10 | axonometric | 4 | 148819 | 56 | 42.926 | 3466.9 |
| 486 | 2025-01-29 21:30:11 | axonometric | 2 | 86808 | 2 | 11.440 | 7588.1 |
| 485 | 2025-01-29 21:30:00 | axonometric | 1 | 49908 | 1 | 2.096 | 23811.1 |
| 484 | 2025-01-29 01:51:49 | axonometric | 3 | 121633 | 15 | 22.206 | 5477.5 |
| 483 | 2025-01-23 02:47:26 | axonometric | 3 | 121633 | 15 | 35.910 | 3387.2 |
| 482 | 2025-01-23 02:47:44 | axonometric | 2 | 86808 | 2 | 11.936 | 7272.8 |
| 481 | 2025-01-23 02:45:17 | axonometric | 1 | 49908 | 1 | 2.203 | 22654.6 |
| 480 | 2025-01-22 18:44:36 | axonometric | 3 | 121633 | 15 | 30.176 | 4030.8 |
| 479 | 2025-01-17 11:37:27 | axonometric | 3 | 121633 | 15 | 29.906 | 4067.2 |
| 478 | 2025-01-16 15:09:20 | axonometric | 3 | 121633 | 15 | 20.656 | 5888.5 |
| 477 | 2025-01-16 15:09:20 | axonometric | 2 | 86808 | 2 | 5.813 | 14933.4 |
| 476 | 2025-01-16 15:08:55 | axonometric | 1 | 49908 | 1 | 5.046 | 9890.6 |
| 475 | 2025-01-13 20:13:43 | axonometric | 4 | 148819 | 56 | 63.783 | 2333.2 |
| 474 | 2025-01-12 19:21:51 | axonometric | 4 | 148819 | 56 | 65.920 | 2257.6 |
| 473 | 2025-01-12 12:20:40 | axonometric | 4 | 148819 | 56 | 49.266 | 3020.7 |
| 472 | 2024-12-29 18:16:11 | axonometric | 4 | 148819 | 56 | 47.250 | 3149.6 |
| 471 | 2024-12-29 18:14:38 | axonometric | 2 | 86808 | 2 | 10.673 | 8133.4 |
| 470 | 2024-12-29 18:14:24 | axonometric | 1 | 49908 | 1 | 4.033 | 12374.9 |
| 469 | 2024-12-21 21:31:47 | axonometric | 3 | 121633 | 15 | 23.830 | 5104.2 |
| 468 | 2024-12-16 21:38:58 | axonometric | 4 | 148819 | 56 | 39.176 | 3798.7 |
| 467 | 2024-12-16 21:38:50 | axonometric | 2 | 86808 | 2 | 2.610 | 33259.8 |
| 466 | 2024-12-16 21:38:42 | axonometric | 1 | 49908 | 1 | 1.343 | 37161.6 |
| 465 | 2024-12-15 21:41:11 | axonometric | 3 | 121633 | 15 | 20.876 | 5826.5 |
| 464 | 2024-12-13 11:05:29 | axonometric | 4 | 148819 | 56 | 46.076 | 3229.9 |
| 463 | 2024-12-13 02:07:45 | axonometric | 4 | 148819 | 56 | 51.843 | 2870.6 |
| 462 | 2024-12-13 02:07:37 | axonometric | 3 | 121633 | 15 | 25.206 | 4825.6 |
| 461 | 2024-12-12 22:15:47 | axonometric | 4 | 148819 | 56 | 39.673 | 3751.1 |
| 460 | 2024-12-12 12:18:29 | axonometric | 4 | 148819 | 56 | 34.860 | 4269.0 |
| 459 | 2024-12-12 12:18:28 | axonometric | 3 | 121633 | 15 | 27.516 | 4420.4 |
| 458 | 2024-12-12 12:18:29 | axonometric | 2 | 86808 | 2 | 11.796 | 7359.1 |
| 457 | 2024-12-12 12:18:21 | axonometric | 1 | 49908 | 1 | 2.016 | 24756.0 |
| 456 | 2024-12-11 16:00:00 | axonometric | 4 | 148819 | 56 | 46.410 | 3206.6 |
| 455 | 2024-12-11 16:00:12 | axonometric | 2 | 86808 | 2 | 20.140 | 4310.2 |
| 454 | 2024-12-11 15:57:26 | axonometric | 1 | 49908 | 1 | 4.763 | 10478.3 |
| 453 | 2024-11-28 04:14:59 | axonometric | 1 | 49908 | 1 | 4.233 | 11790.2 |
| 452 | 2024-11-15 01:35:13 | axonometric | 3 | 121633 | 15 | 23.673 | 5138.0 |
| 451 | 2024-11-13 07:13:47 | axonometric | 4 | 148819 | 56 | 41.736 | 3565.7 |
| 450 | 2024-11-12 18:57:55 | axonometric | 4 | 148819 | 56 | 59.566 | 2498.4 |
| 449 | 2024-11-11 17:18:26 | axonometric | 4 | 148819 | 56 | 50.220 | 2963.3 |
| 448 | 2024-11-09 07:51:15 | axonometric | 4 | 148819 | 56 | 60.646 | 2453.9 |
| 447 | 2024-11-09 07:51:14 | axonometric | 4 | 148819 | 56 | 36.736 | 4051.0 |
| 446 | 2024-11-09 07:51:15 | axonometric | 3 | 121633 | 15 | 26.376 | 4611.5 |
| 445 | 2024-11-09 07:51:14 | axonometric | 2 | 86808 | 2 | 13.970 | 6213.9 |
| 444 | 2024-11-09 06:34:08 | axonometric | 1 | 49908 | 1 | 0.780 | 63984.6 |
| 443 | 2024-10-20 17:31:36 | axonometric | 1 | 49908 | 1 | 1.686 | 29601.4 |
| 442 | 2024-10-13 23:14:55 | axonometric | 3 | 121633 | 15 | 25.190 | 4828.6 |
| 441 | 2024-10-12 15:51:25 | axonometric | 4 | 148819 | 56 | 48.550 | 3065.3 |