History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"breeds"
Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
615 | 2025-10-14 12:59:06 | breeds | 2 | 82551 | 113 | 2.170 | 38041.9 |
614 | 2025-10-12 15:40:17 | breeds | 2 | 82551 | 113 | 4.156 | 19863.1 |
613 | 2025-10-07 08:43:16 | breeds | 2 | 82551 | 113 | 2.436 | 33887.9 |
612 | 2025-10-03 08:03:09 | breeds | 1 | 48755 | 10 | 0.766 | 63648.8 |
611 | 2025-09-28 18:54:58 | breeds | 2 | 82551 | 113 | 2.220 | 37185.1 |
610 | 2025-09-27 03:41:54 | breeds | 1 | 48755 | 10 | 0.860 | 56691.9 |
609 | 2025-09-26 10:50:59 | breeds | 1 | 48755 | 10 | 0.843 | 57835.1 |
608 | 2025-09-25 02:11:43 | breeds | 1 | 48755 | 10 | 0.906 | 53813.5 |
607 | 2025-09-25 01:58:22 | breeds | 1 | 48755 | 10 | 4.013 | 12149.3 |
606 | 2025-09-24 05:21:13 | breeds | 1 | 48755 | 10 | 0.860 | 56691.9 |
605 | 2025-09-22 11:03:15 | breeds | 1 | 48755 | 10 | 0.813 | 59969.2 |
604 | 2025-09-21 12:37:49 | breeds | 2 | 82551 | 113 | 2.393 | 34496.9 |
603 | 2025-09-20 05:58:33 | breeds | 1 | 48755 | 10 | 0.860 | 56691.9 |
602 | 2025-09-19 06:04:45 | breeds | 1 | 48755 | 10 | 0.873 | 55847.7 |
601 | 2025-09-18 19:40:25 | breeds | 1 | 48755 | 10 | 0.860 | 56691.9 |
600 | 2025-09-18 04:06:26 | breeds | 1 | 48755 | 10 | 0.890 | 54780.9 |
599 | 2025-09-17 17:44:58 | breeds | 1 | 48755 | 10 | 0.983 | 49598.2 |
598 | 2025-09-17 17:44:49 | breeds | 1 | 48755 | 10 | 0.843 | 57835.1 |
597 | 2025-09-16 21:55:08 | breeds | 1 | 48755 | 10 | 0.843 | 57835.1 |
596 | 2025-09-13 17:55:26 | breeds | 1 | 48755 | 10 | 0.843 | 57835.1 |
595 | 2025-09-13 14:16:54 | breeds | 1 | 48755 | 10 | 0.873 | 55847.7 |
594 | 2025-09-10 06:24:45 | breeds | 1 | 48755 | 10 | 0.750 | 65006.7 |
593 | 2025-09-07 05:34:32 | breeds | 2 | 82551 | 113 | 2.326 | 35490.5 |
592 | 2025-09-06 23:33:36 | breeds | 1 | 48755 | 10 | 0.876 | 55656.4 |
591 | 2025-09-03 16:21:06 | breeds | 1 | 48755 | 10 | 0.860 | 56691.9 |
590 | 2025-09-03 12:48:09 | breeds | 1 | 48755 | 10 | 0.796 | 61250.0 |
589 | 2025-08-31 09:11:09 | breeds | 1 | 48755 | 10 | 0.843 | 57835.1 |
588 | 2025-08-28 01:52:44 | breeds | 1 | 48755 | 10 | 0.843 | 57835.1 |
587 | 2025-08-25 02:27:40 | breeds | 1 | 48755 | 10 | 4.046 | 12050.2 |
586 | 2025-08-24 18:19:05 | breeds | 1 | 48755 | 10 | 2.670 | 18260.3 |
585 | 2025-08-21 12:39:09 | breeds | 2 | 82551 | 113 | 6.736 | 12255.2 |
584 | 2025-08-18 00:49:40 | breeds | 1 | 48755 | 10 | 0.856 | 56956.8 |
583 | 2025-08-16 02:44:34 | breeds | 2 | 82551 | 113 | 2.233 | 36968.7 |
582 | 2025-08-14 16:34:11 | breeds | 1 | 48755 | 10 | 0.826 | 59025.4 |
581 | 2025-08-07 22:44:02 | breeds | 1 | 48755 | 10 | 0.906 | 53813.5 |
580 | 2025-08-02 09:28:17 | breeds | 2 | 82551 | 113 | 5.236 | 15766.0 |
579 | 2025-08-01 15:54:03 | breeds | 1 | 48755 | 10 | 2.690 | 18124.5 |
578 | 2025-08-01 07:11:18 | breeds | 2 | 82551 | 113 | 17.890 | 4614.4 |
577 | 2025-08-01 05:54:06 | breeds | 1 | 48755 | 10 | 6.173 | 7898.1 |
576 | 2025-07-31 11:12:26 | breeds | 2 | 82551 | 113 | 12.013 | 6871.8 |
575 | 2025-07-24 02:57:14 | breeds | 1 | 48755 | 10 | 4.330 | 11259.8 |
574 | 2025-07-23 06:39:20 | breeds | 1 | 48755 | 10 | 2.296 | 21234.8 |
573 | 2025-07-22 17:48:05 | breeds | 1 | 48755 | 10 | 4.080 | 11949.8 |
572 | 2025-07-22 15:11:46 | breeds | 1 | 48755 | 10 | 4.860 | 10031.9 |
571 | 2025-07-22 06:54:53 | breeds | 2 | 82551 | 113 | 13.233 | 6238.3 |
570 | 2025-07-22 06:42:18 | breeds | 2 | 82551 | 113 | 13.360 | 6179.0 |
569 | 2025-07-22 05:19:25 | breeds | 1 | 48755 | 10 | 0.810 | 60191.4 |
568 | 2025-07-18 21:45:51 | breeds | 2 | 82551 | 113 | 7.546 | 10939.7 |
567 | 2025-07-18 21:03:56 | breeds | 2 | 82551 | 113 | 7.763 | 10633.9 |
566 | 2025-07-18 07:50:41 | breeds | 1 | 48755 | 10 | 2.580 | 18897.3 |
565 | 2025-07-17 09:00:39 | breeds | 2 | 82551 | 113 | 9.546 | 8647.7 |
564 | 2025-07-17 08:58:44 | breeds | 1 | 48755 | 10 | 2.080 | 23439.9 |
563 | 2025-07-13 04:59:59 | breeds | 1 | 48755 | 10 | 0.890 | 54780.9 |
562 | 2025-07-12 20:34:01 | breeds | 1 | 48755 | 10 | 1.470 | 33166.7 |
561 | 2025-07-12 05:12:23 | breeds | 1 | 48755 | 10 | 0.890 | 54780.9 |
560 | 2025-07-08 21:06:08 | breeds | 1 | 48755 | 10 | 0.843 | 57835.1 |
559 | 2025-07-05 04:16:41 | breeds | 1 | 48755 | 10 | 5.580 | 8737.5 |
558 | 2025-07-02 14:57:27 | breeds | 1 | 48755 | 10 | 1.940 | 25131.4 |
557 | 2025-06-30 00:04:47 | breeds | 2 | 82551 | 113 | 7.233 | 11413.1 |
556 | 2025-06-29 03:31:58 | breeds | 1 | 48755 | 10 | 0.843 | 57835.1 |
555 | 2025-06-28 23:04:26 | breeds | 1 | 48755 | 10 | 4.500 | 10834.4 |
554 | 2025-06-28 20:09:04 | breeds | 1 | 48755 | 10 | 0.860 | 56691.9 |
553 | 2025-06-28 04:20:20 | breeds | 2 | 82551 | 113 | 16.516 | 4998.2 |
552 | 2025-06-26 18:44:32 | breeds | 2 | 82551 | 113 | 16.126 | 5119.1 |
551 | 2025-06-21 07:03:08 | breeds | 1 | 48755 | 10 | 6.373 | 7650.2 |
550 | 2025-06-21 02:31:54 | breeds | 1 | 48755 | 10 | 2.736 | 17819.8 |
549 | 2025-06-19 08:00:50 | breeds | 2 | 82551 | 113 | 15.936 | 5180.2 |
548 | 2025-06-19 04:36:23 | breeds | 2 | 82551 | 113 | 12.860 | 6419.2 |
547 | 2025-06-13 22:26:56 | breeds | 2 | 82551 | 113 | 17.533 | 4708.3 |
546 | 2025-06-12 03:27:30 | breeds | 1 | 48755 | 10 | 5.876 | 8297.3 |
545 | 2025-06-12 01:34:37 | breeds | 1 | 48755 | 10 | 4.300 | 11338.4 |
544 | 2025-06-10 17:00:10 | breeds | 2 | 82551 | 113 | 14.906 | 5538.1 |
543 | 2025-06-10 14:12:24 | breeds | 2 | 82551 | 113 | 15.080 | 5474.2 |
542 | 2025-06-10 01:32:22 | breeds | 1 | 48755 | 10 | 2.376 | 20519.8 |
541 | 2025-06-08 16:53:44 | breeds | 2 | 82551 | 113 | 7.923 | 10419.2 |
540 | 2025-06-04 05:37:41 | breeds | 1 | 48755 | 10 | 1.843 | 26454.2 |
539 | 2025-06-02 13:54:58 | breeds | 1 | 48755 | 10 | 4.140 | 11776.6 |
538 | 2025-06-01 07:42:40 | breeds | 1 | 48755 | 10 | 1.750 | 27860.0 |
537 | 2025-05-29 23:05:03 | breeds | 2 | 82551 | 113 | 2.703 | 30540.5 |
536 | 2025-05-28 04:59:25 | breeds | 1 | 48755 | 10 | 0.906 | 53813.5 |
535 | 2025-05-28 02:32:57 | breeds | 1 | 48755 | 10 | 1.780 | 27390.4 |
534 | 2025-05-28 01:17:36 | breeds | 2 | 82551 | 113 | 2.296 | 35954.3 |
533 | 2025-05-26 11:47:01 | breeds | 2 | 82551 | 113 | 6.330 | 13041.2 |
532 | 2025-05-23 12:10:42 | breeds | 1 | 48755 | 10 | 0.750 | 65006.7 |
531 | 2025-05-23 02:00:35 | breeds | 1 | 48755 | 10 | 0.750 | 65006.7 |
530 | 2025-05-20 02:20:50 | breeds | 1 | 48755 | 10 | 2.720 | 17924.6 |
529 | 2025-05-12 04:10:58 | breeds | 1 | 48755 | 10 | 6.206 | 7856.1 |
528 | 2025-05-08 04:06:02 | breeds | 1 | 48755 | 10 | 3.156 | 15448.4 |
527 | 2025-05-04 05:39:44 | breeds | 1 | 48755 | 10 | 4.143 | 11768.0 |
526 | 2025-05-02 15:59:03 | breeds | 1 | 48755 | 10 | 5.686 | 8574.6 |
525 | 2025-05-02 13:56:20 | breeds | 1 | 48755 | 10 | 4.046 | 12050.2 |
524 | 2025-04-30 12:26:05 | breeds | 1 | 48755 | 10 | 4.360 | 11182.3 |
523 | 2025-04-30 02:08:46 | breeds | 1 | 48755 | 10 | 3.326 | 14658.7 |
522 | 2025-04-21 13:54:09 | breeds | 2 | 82551 | 113 | 16.436 | 5022.6 |
521 | 2025-04-20 03:35:31 | breeds | 2 | 82551 | 113 | 9.940 | 8304.9 |
520 | 2025-04-19 01:28:59 | breeds | 1 | 48755 | 10 | 0.920 | 52994.6 |
519 | 2025-04-18 15:45:07 | breeds | 2 | 82551 | 113 | 9.940 | 8304.9 |
518 | 2025-04-16 15:40:48 | breeds | 2 | 82551 | 113 | 13.423 | 6150.0 |
517 | 2025-04-11 04:07:10 | breeds | 1 | 48755 | 10 | 1.843 | 26454.2 |
516 | 2025-04-04 05:30:33 | breeds | 1 | 48755 | 10 | 2.470 | 19738.9 |