129:(RTO), the maximum expected time a database is expected to be unavailable due to interruption, by methods which involve copying files from disk or other storage archives. To overcome these issues techniques such as clustering, cloned/replicated/standby databases, file-snapshots, storage snapshots or a backup manager may help achieve the RTO and availability, although individual methods may have limitations, caveats, license, and infrastructure requirements while some may risk data loss and not meet the recovery point objective (RPO). For many systems only geographically remote solutions may be acceptable.
1625:
1615:
87:
say that any database with more than 1 TB of data is considered a VLDB. This absolute amount of data has varied over time as computer processing, storage and backup methods have become better able to handle larger amounts of data. That said, VLDB issues may start to appear when 1 TB is
124:
When dealing with VLDB operations relating to maintenance and recovery such as database reorganizations and file copies which were quite practical on a non-VLDB take very significant amounts of time and resources for a VLDB database. In particular it typically infeasible to meet a typical
984:
864:
Brooks, Charlotte; Leung, Clem; Mirza, Aslam; Neal, Curtis; Qiu, Yin Lei; Sing, John; Wong, Francis TH; Wright, Ian R (March 2007). "Chapter 1. Three
Business solution segments defined".
894:
812:
665:
1068:
75:
One definition has suggested that a database has become a VLDB when it is "too large to be maintained within the window of opportunity… the time when the database is quiet".
717:
1160:
20:
1112:
925:
40:, is a database that contains a very large amount of data, so much that it can require specialized architectural, management, processing and maintenance methodologies.
544:
176:
Should an increase in database size cause the number of accessors of the database to increase then more server and network resources may be consumed, and the risk of
780:
573:
244:
The increasing size of a VLDB may put pressure on server and network resources and a bottleneck may appear that may require infrastructure investment to resolve.
56:
allow for a broad and subjective interpretation, but attempts at defining a metric and threshold have been made. Early metrics were the size of the database in a
747:
1520:
601:
627:
266:
were designed from the start to support large volumes of data, so database administrators may not encounter VLDB issues that older versions of traditional
96:
Key areas where a VLDB may present challenges include configuration, storage, performance, maintenance, administration, availability and server resources.
337:
1417:
842:
890:
1199:
978:
803:
953:. 7th International Conference on Cloud Computing and Services. Vol. 1: CLOSER. SCITEPRESS – Science and Technology Publications, Lda.
1550:
1360:
1002:
1535:
950:
High
Availability and Performance of Database in the Cloud - Traditional Master-slave Replication versus Modern Cluster-based Solutions
398:
1232:
873:
687:
518:
423:
Encyclopedia of
Computer Science and Technology: Volume 14 - Very Large Data Base Systems to Zero-Memory and Markov Information Source
1618:
657:
431:
137:
Best practice is for backup and recovery to be architectured in terms of the overall availability and business continuity solution.
1056:
204:
Partitioning may be able assist the performance of bulk operations on a VLDB including backup and recovery., bulk movements due to
104:
Careful configuration of databases that lie in the VLDB realm is necessary to alleviate or reduce issues raised by VLDB databases.
153:); while the indexes used to access data may grow slightly in height requiring perhaps an extra storage access to reach the data (
205:
709:
149:
as database size increases. Some accesses will simply have more data to process (scan) which will take proportionally longer (
1152:
1545:
1530:
1099:
917:
1459:
1413:
535:
1566:
189:
1033:
771:
1525:
1380:
1327:
1137:
566:
358:
Gaines, R. S. and R. Gammill. Very Large Data Bases: An
Emerging Research Area, Informal working paper, RAND Corporation
1653:
1438:
1322:
739:
594:
619:
1581:
1454:
1350:
1270:
146:
1186:. 2013 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM). IEEE. p. 15.
1648:
1540:
1345:
1057:"Oracle Partitioning in Oracle Database 12c Release 2 Extreme Data Management and Performance for every System"
299:
1475:
126:
1423:
1312:
1225:
113:
61:
1497:
221:
217:
329:
300:"Oracle Database Online Documentation 11g Release 1 (11.1) / Database Administration Database Concepts"
1571:
1433:
1290:
1131:
834:
181:
145:
Given the same infrastructure there may typically be a decrease in performance, that is increase in
1591:
1295:
225:
1628:
1512:
1502:
1390:
998:
478:
1596:
1576:
1395:
1372:
1218:
1195:
974:
869:
514:
470:
427:
233:
158:
1485:
1305:
1275:
1187:
1055:
964:
954:
802:
770:
534:
460:
390:
368:
298:
193:
185:
177:
695:
1480:
1428:
1405:
1317:
1285:
1280:
1260:
154:
1492:
1385:
1355:
1265:
162:
88:
approached, and are more than likely to have appeared as 30 TB or so is exceeded.
57:
208:(ILM), reducing contention as well as allowing optimization of some query processing.
161:
becoming less efficient because proportionally less data can be cached and while some
1642:
948:
507:
501:
1601:
656:
Furman, Dimitri (22 January 2018). Rajesh Setlem; Mike Weiner; Xiaochen Wu (eds.).
567:"The Very Large Database Problem - How to Backup & Recover 30–100 TB Databases"
482:
19:
This article is about databases which are very large. For the VLDB conference, see
421:
369:
262:
may involve a VLDB database. That said some of the storage solutions supporting
1191:
150:
1300:
1025:
229:
170:
959:
474:
1586:
465:
448:
166:
1337:
1255:
1241:
1101:
Get the best out of Oracle
Partitioning - A practical guide and reference
254:
889:
Akhtar, Ali Navid; Buchholtz, Jeff; Ryan, Michael; Setty, Kumar (2012).
83:
There is no absolute amount of data that can be cited. For example, one
112:
The complexities of managing a VLDB can increase exponentially for the
969:
68:. Technology improvements have continually changed what is considered
595:"Tuning & Applying Best Practices On Very Large Databases (VLDB)"
65:
267:
449:"On some metrics for databases or what is a very large database?"
688:"Specialized Requirements for Relational Data Warehouse Servers"
279:
180:
will increase. Some solutions to regaining performance include
1214:
499:
Rankins, Ray; Jensen, Paul; Bertucci, Paul (18 December 2002).
918:"Understanding B+tree Indexes and how they Impact Performance"
866:
IBM System
Storage Business Continuity: Part 2 Solutions Guide
620:"Top 10 Must-Do Items for your SQL Server Very Large Database"
1151:
Steel, Phil; Poggemeyer, Liza; Plett, Corey (1 August 2018).
447:
Gerritsen, Rob; Morgan, Howard; Zisman, Michael (June 1977).
1210:
536:"Oracle Database Release 18 - VLDB and Partitioning Guide"
375:. North American Publishing Company. 1964. p. 18,58.
169:
automatically sustain well with growth others such as a
1111:. Hermann Bär. 40-S2-C01 - Salle Curie (CERN): Oracle.
1559:
1511:
1468:
1447:
1404:
1371:
1336:
1248:
1184:
A performance comparison of SQL and NoSQL databases
506:
500:
16:Database that contains a very large amount of data
658:"SQL Server VLDB in Azure: DBA Tasks Made Simple"
216:In order to satisfy needs of a VLDB the database
64:or the time for a full database operation like a
21:International Conference on Very Large Data Bases
1093:
1091:
1089:
523:. Administering Very Large SQL Server Databases.
651:
649:
647:
645:
1226:
1182:Li, Yishan; Manoharan, Sathiamoorthy (2013).
891:"Database Backup and Recovery Best Practices"
835:"Chapter 1 High Availability and Scalability"
494:
492:
8:
1153:"Server Hardware Performance Considerations"
588:
586:
1233:
1219:
1211:
543:. 1 Introduction to Very Large Databases.
968:
958:
464:
384:
382:
324:
322:
804:"Using a split mirror as a backup image"
290:
1129:
579:from the original on 19 February 2018.
1074:from the original on 15 December 2017
987:from the original on 17 October 2018.
845:from the original on 15 December 2016
783:from the original on 7 September 2018
740:"Cross Datacenter Replication (XDCR)"
630:from the original on 13 December 2017
7:
1163:from the original on 17 October 2018
1118:from the original on 12 October 2018
928:from the original on 7 February 2018
750:from the original on 17 October 2018
720:from the original on 17 October 2018
607:from the original on 4 October 2018.
389:Widlake, Marin (18 September 2009).
1614:
1001:. Definition of: database machine.
815:from the original on 9 January 2018
668:from the original on 6 October 2018
547:from the original on 3 October 2018
401:from the original on 6 October 2018
1024:Burleson, Donald (26 March 2015).
14:
1098:Teske, Thomas (8 February 2018).
1036:from the original on 30 June 2017
897:from the original on 29 June 2018
618:Chaves, Warner (7 January 2015).
420:Sidley, Edgar H. (1 April 1980).
1624:
1623:
1613:
1005:from the original on 4 July 2016
340:from the original on 4 July 2018
307:. 18 Very Large Databases (VLDB)
206:information lifecycle management
710:"Cluster design considerations"
694:. 21 June 1996. Archived from
1:
1567:Database-centric architecture
916:Tariq, Ovais (14 July 2011).
593:Hussain, Syed Jaffer (2014).
426:. CRC Press. pp. 1–18.
330:"Very Large Database (VLDB)"
258:, but the storage aspect of
120:Availability and maintenance
116:as database size increases.
1192:10.1109/PACRIM.2013.6625441
772:"Snapshots Are NOT Backups"
1670:
1582:Locks with ordered sharing
1414:Entities and relationships
1271:Database management system
18:
1610:
1460:Object–relational mapping
1026:"Oracle Backup VLDB tips"
509:Microsoft SQL Server 2000
220:needs to have low access
157:). Other effects can be
1136:: CS1 maint: location (
960:10.5220/0006294604130420
371:Data Processing Magazine
252:VLDB is not the same as
248:Relationship to big data
173:may need to be rebuilt.
79:Sizes of a VLDB database
48:The vague adjectives of
1157:Microsoft IT Pro Center
947:Shrestha, Raju (2017).
127:recovery time objective
692:Red Brick Systems, Inc
513:(2nd ed.). SAMS.
114:database administrator
62:database normalization
32:, (originally written
1361:information retrieval
466:10.1145/984382.984393
1572:Intelligent database
809:IBM Knowledge Center
270:'s might encounter.
34:very large data base
1381:Activity monitoring
1030:Burleson Consulting
698:on 10 October 1997.
133:Backup and recovery
30:very large database
1654:Types of databases
1551:Online real estate
777:Oracle technetwork
1636:
1635:
1597:Halloween Problem
1577:Two-phase locking
1536:Facial expression
1455:Abstraction layer
1396:Negative database
1351:Data manipulation
1201:978-1-4799-1501-9
980:978-989-758-243-1
600:. Sangam: AIOUG.
453:ACM SIGMOD Record
391:"What is a VLDB?"
234:high availability
1661:
1627:
1626:
1617:
1616:
1235:
1228:
1221:
1212:
1206:
1205:
1179:
1173:
1172:
1170:
1168:
1148:
1142:
1141:
1135:
1127:
1125:
1123:
1117:
1106:
1095:
1084:
1083:
1081:
1079:
1073:
1062:
1059:
1052:
1046:
1045:
1043:
1041:
1021:
1015:
1014:
1012:
1010:
995:
989:
988:
972:
962:
944:
938:
937:
935:
933:
913:
907:
906:
904:
902:
886:
880:
879:
868:. IBM Redbooks.
861:
855:
854:
852:
850:
831:
825:
824:
822:
820:
806:
799:
793:
792:
790:
788:
774:
766:
760:
759:
757:
755:
736:
730:
729:
727:
725:
706:
700:
699:
684:
678:
677:
675:
673:
653:
640:
639:
637:
635:
615:
609:
608:
606:
599:
590:
581:
580:
578:
571:
563:
557:
556:
554:
552:
538:
531:
525:
524:
512:
504:
496:
487:
486:
468:
444:
438:
437:
417:
411:
410:
408:
406:
386:
377:
376:
374:
365:
359:
356:
350:
349:
347:
345:
326:
317:
316:
314:
312:
302:
295:
240:Server resources
194:database machine
188:, possibly with
1669:
1668:
1664:
1663:
1662:
1660:
1659:
1658:
1649:Data management
1639:
1638:
1637:
1632:
1606:
1555:
1507:
1464:
1443:
1400:
1367:
1346:Data definition
1332:
1244:
1239:
1209:
1202:
1181:
1180:
1176:
1166:
1164:
1150:
1149:
1145:
1128:
1121:
1119:
1115:
1104:
1097:
1096:
1087:
1077:
1075:
1071:
1060:
1054:
1053:
1049:
1039:
1037:
1023:
1022:
1018:
1008:
1006:
997:
996:
992:
981:
946:
945:
941:
931:
929:
915:
914:
910:
900:
898:
888:
887:
883:
876:
863:
862:
858:
848:
846:
833:
832:
828:
818:
816:
801:
800:
796:
786:
784:
768:
767:
763:
753:
751:
738:
737:
733:
723:
721:
708:
707:
703:
686:
685:
681:
671:
669:
655:
654:
643:
633:
631:
617:
616:
612:
604:
597:
592:
591:
584:
576:
569:
565:
564:
560:
550:
548:
533:
532:
528:
521:
498:
497:
490:
446:
445:
441:
434:
419:
418:
414:
404:
402:
388:
387:
380:
367:
366:
362:
357:
353:
343:
341:
328:
327:
320:
310:
308:
297:
296:
292:
288:
276:
250:
242:
214:
202:
155:sub-linear time
143:
135:
122:
110:
102:
94:
92:VLDB challenges
81:
46:
24:
17:
12:
11:
5:
1667:
1665:
1657:
1656:
1651:
1641:
1640:
1634:
1633:
1611:
1608:
1607:
1605:
1604:
1599:
1594:
1589:
1584:
1579:
1574:
1569:
1563:
1561:
1557:
1556:
1554:
1553:
1548:
1543:
1538:
1533:
1528:
1523:
1517:
1515:
1509:
1508:
1506:
1505:
1500:
1495:
1490:
1489:
1488:
1478:
1476:Virtualization
1472:
1470:
1466:
1465:
1463:
1462:
1457:
1451:
1449:
1445:
1444:
1442:
1441:
1436:
1431:
1426:
1421:
1410:
1408:
1402:
1401:
1399:
1398:
1393:
1388:
1383:
1377:
1375:
1369:
1368:
1366:
1365:
1364:
1363:
1353:
1348:
1342:
1340:
1334:
1333:
1331:
1330:
1325:
1320:
1315:
1310:
1309:
1308:
1303:
1293:
1288:
1283:
1278:
1273:
1268:
1263:
1258:
1252:
1250:
1246:
1245:
1240:
1238:
1237:
1230:
1223:
1215:
1208:
1207:
1200:
1174:
1143:
1085:
1067:. March 2017.
1047:
1016:
999:"Encyclopedia"
990:
979:
939:
922:ovaistariq.net
908:
881:
875:978-0738489728
874:
856:
826:
794:
761:
731:
701:
679:
641:
610:
582:
558:
526:
520:978-0672324673
519:
488:
439:
432:
412:
378:
360:
351:
318:
289:
287:
284:
283:
282:
275:
272:
249:
246:
241:
238:
213:
210:
201:
198:
192:, or use of a
142:
139:
134:
131:
121:
118:
109:
108:Administration
106:
101:
98:
93:
90:
80:
77:
58:canonical form
45:
42:
15:
13:
10:
9:
6:
4:
3:
2:
1666:
1655:
1652:
1650:
1647:
1646:
1644:
1631:
1630:
1621:
1620:
1609:
1603:
1600:
1598:
1595:
1593:
1590:
1588:
1585:
1583:
1580:
1578:
1575:
1573:
1570:
1568:
1565:
1564:
1562:
1558:
1552:
1549:
1547:
1544:
1542:
1539:
1537:
1534:
1532:
1529:
1527:
1524:
1522:
1519:
1518:
1516:
1514:
1510:
1504:
1501:
1499:
1496:
1494:
1491:
1487:
1484:
1483:
1482:
1479:
1477:
1474:
1473:
1471:
1467:
1461:
1458:
1456:
1453:
1452:
1450:
1446:
1440:
1437:
1435:
1432:
1430:
1427:
1425:
1424:Normalization
1422:
1419:
1415:
1412:
1411:
1409:
1407:
1403:
1397:
1394:
1392:
1389:
1387:
1384:
1382:
1379:
1378:
1376:
1374:
1370:
1362:
1359:
1358:
1357:
1354:
1352:
1349:
1347:
1344:
1343:
1341:
1339:
1335:
1329:
1326:
1324:
1321:
1319:
1316:
1314:
1313:Administrator
1311:
1307:
1304:
1302:
1299:
1298:
1297:
1294:
1292:
1289:
1287:
1284:
1282:
1279:
1277:
1274:
1272:
1269:
1267:
1264:
1262:
1259:
1257:
1254:
1253:
1251:
1247:
1243:
1236:
1231:
1229:
1224:
1222:
1217:
1216:
1213:
1203:
1197:
1193:
1189:
1185:
1178:
1175:
1162:
1158:
1154:
1147:
1144:
1139:
1133:
1114:
1110:
1103:
1102:
1094:
1092:
1090:
1086:
1070:
1066:
1058:
1051:
1048:
1035:
1031:
1027:
1020:
1017:
1004:
1000:
994:
991:
986:
982:
976:
971:
966:
961:
956:
952:
951:
943:
940:
927:
923:
919:
912:
909:
896:
892:
885:
882:
877:
871:
867:
860:
857:
844:
840:
836:
830:
827:
814:
810:
805:
798:
795:
782:
778:
773:
765:
762:
749:
745:
741:
735:
732:
719:
715:
711:
705:
702:
697:
693:
689:
683:
680:
667:
663:
659:
652:
650:
648:
646:
642:
629:
625:
621:
614:
611:
603:
596:
589:
587:
583:
575:
568:
562:
559:
546:
542:
537:
530:
527:
522:
516:
511:
510:
503:
495:
493:
489:
484:
480:
476:
472:
467:
462:
458:
454:
450:
443:
440:
435:
433:9780824722142
429:
425:
424:
416:
413:
400:
396:
392:
385:
383:
379:
373:
372:
364:
361:
355:
352:
339:
335:
331:
325:
323:
319:
306:
301:
294:
291:
285:
281:
278:
277:
273:
271:
269:
265:
261:
257:
256:
247:
245:
239:
237:
235:
231:
227:
223:
219:
211:
209:
207:
199:
197:
195:
191:
187:
183:
179:
174:
172:
168:
164:
160:
156:
152:
148:
147:response time
140:
138:
132:
130:
128:
119:
117:
115:
107:
105:
100:Configuration
99:
97:
91:
89:
86:
78:
76:
73:
71:
67:
63:
59:
55:
51:
43:
41:
39:
35:
31:
26:
22:
1622:
1612:
1602:Log shipping
1546:Online music
1531:Biodiversity
1498:Preservation
1256:Requirements
1183:
1177:
1165:. Retrieved
1156:
1146:
1120:. Retrieved
1108:
1100:
1076:. Retrieved
1064:
1050:
1038:. Retrieved
1029:
1019:
1007:. Retrieved
993:
949:
942:
930:. Retrieved
921:
911:
899:. Retrieved
884:
865:
859:
847:. Retrieved
838:
829:
817:. Retrieved
808:
797:
785:. Retrieved
776:
769:Chien, Tim.
764:
752:. Retrieved
743:
734:
722:. Retrieved
713:
704:
696:the original
691:
682:
670:. Retrieved
661:
632:. Retrieved
623:
613:
561:
549:. Retrieved
540:
529:
508:
459:(1): 50–74.
456:
452:
442:
422:
415:
403:. Retrieved
394:
370:
363:
354:
342:. Retrieved
333:
309:. Retrieved
304:
293:
263:
259:
253:
251:
243:
215:
203:
200:Partitioning
182:partitioning
175:
165:such as the
144:
136:
123:
111:
103:
95:
84:
82:
74:
69:
53:
49:
47:
37:
33:
29:
27:
25:
1619:WikiProject
1448:Programming
1439:Cardinality
1434:Refactoring
1291:Application
1132:cite speech
572:. actifio.
334:Technopedia
151:linear time
141:Performance
1643:Categories
1592:Publishing
1526:Biological
1469:Management
1301:datasource
1296:Connection
1167:17 October
1122:12 October
1107:(Speech).
1078:17 October
1040:11 October
1009:10 October
970:10642/6140
932:10 October
901:12 October
849:12 October
819:10 October
787:10 October
754:17 October
744:Crouchbase
724:17 October
714:Crouchbase
286:References
230:throughput
226:contention
186:clustering
178:contention
171:hash table
70:very large
44:Definition
1587:Load file
1503:Integrity
1493:Migration
1420:notation)
1391:Forensics
1338:Languages
839:dev.mysql
672:6 October
634:5 October
551:3 October
475:0163-5808
405:7 October
344:3 October
311:3 October
1629:Category
1560:See also
1521:Academic
1513:Lists of
1418:Enhanced
1373:Security
1242:Database
1161:Archived
1113:Archived
1069:Archived
1034:Archived
1003:Archived
985:Archived
926:Archived
895:Archived
843:Archived
813:Archived
781:Archived
748:Archived
718:Archived
666:Archived
628:Archived
624:SQLTURBO
602:Archived
574:Archived
545:Archived
399:Archived
395:mwidlake
338:Archived
274:See also
264:big data
260:big data
255:big data
190:sharding
1486:caching
1276:Machine
483:6359244
228:, high
222:latency
218:storage
212:Storage
163:indexes
159:caching
1541:Online
1481:Tuning
1429:Schema
1406:Design
1286:Server
1281:Engine
1266:Models
1261:Theory
1198:
1065:Oracle
977:
872:
541:Oracle
517:
481:
473:
430:
305:oracle
232:, and
85:cannot
66:backup
1416:(and
1386:Audit
1356:Query
1328:Tools
1323:Types
1116:(PDF)
1105:(PDF)
1072:(PDF)
1061:(PDF)
605:(PDF)
598:(PDF)
577:(PDF)
570:(PDF)
479:S2CID
268:RDBMS
54:large
36:) or
1318:Lock
1249:Main
1196:ISBN
1169:2018
1138:link
1124:2018
1109:Cern
1080:2018
1042:2016
1011:2018
975:ISBN
934:2018
903:2012
870:ISBN
851:2018
821:2018
789:2018
756:2017
726:2017
674:2018
662:MSDN
636:2018
553:2018
515:ISBN
502:"21"
471:ISSN
428:ISBN
407:2018
346:2018
313:2018
280:XLDB
224:and
60:via
52:and
50:very
38:VLDB
1306:DSN
1188:doi
965:hdl
955:doi
461:doi
1645::
1194:.
1159:.
1155:.
1134:}}
1130:{{
1088:^
1063:.
1032:.
1028:.
983:.
973:.
963:.
924:.
920:.
893:.
841:.
837:.
811:.
807:.
779:.
775:.
746:.
742:.
716:.
712:.
690:.
664:.
660:.
644:^
626:.
622:.
585:^
539:.
505:.
491:^
477:.
469:.
455:.
451:.
397:.
393:.
381:^
336:.
332:.
321:^
303:.
236:.
196:.
184:,
167:B+
72:.
28:A
1234:e
1227:t
1220:v
1204:.
1190::
1171:.
1140:)
1126:.
1082:.
1044:.
1013:.
967::
957::
936:.
905:.
878:.
853:.
823:.
791:.
758:.
728:.
676:.
638:.
555:.
485:.
463::
457:9
436:.
409:.
348:.
315:.
23:.
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.