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1
Commodity Database Servers
Jim Gray
Microsoft Research
Gray@Microsoft.com
http://Research.Microsoft.com/~Gray/talks
2
Outline
• Status report on Commodity Server Performance
• Why Most VLDBs will be Multi-Media Servers
• Preview of Microsoft’s SQL Server 7
3
Status Report on Commodity Server Performance
• Standards: – TPC, – SpecWeb, ...
• Product benchmarks: e.g. – SAP, – PeopleSoft,…
• Both indicate that – NT is 18 months behind Unix-SMP performance – but clusters can make up the difference
4
TPC-CSMP
• HP 9000 16 cpu, Sybase 1152.1 ktpmC, 82$/tpmC
• NEC 8 cpuSQL Server14.9 ktpmC, 60$/tpmC
Cluster• IBM SP2 12x8 cpu
Oracle 8.257 ktpmC, 148$/tpmc
• Predict:large & inexpensive NT cluster number this year.
Diseconomy of Scale: Big systems are Expensive
27$/tpmC vs 148$/tpmC
0
5
10
15
20
25
30
35
40
11007 16101 52117 57053
tpmC
tpm
C p
er
k$
5
TPC-D• Performance Champions:NCR/Teradata
– 1 TB:32x4 node clusters
– 300 GB: 24x4 node cluster
– 100 GB: 8x4 cluster
• All use Teradata software on NCR World-Mark Intel-based hardware
(QppD) (QthD)1,000 GB NCR WorlkMark Server 3069 1205
300 GB NCR WorlkMark Server 9260 3117100 GB NCR WorldMark Server 12149 3912
6
Outline
• Status report on Commodity Server Performance
• Why Most VLDBs will be Multi-Media Servers
• Preview of Microsoft’s SQL Server 7
7
VLDB Reality Test
• California DMV – ~ 20 million cars, drivers, doctors,
barbers,..
– Some drivers have moving violations
– DMV knows about 1.5 KB about each one
– 30 GB total.
• Microsoft: too big says DoJ– 40B$ revenue (in company life time)
– ~1 billion unit sales: @ 100 B = 100 GB
– ~100 M customers: @1 KB = 100 GB
• Wall Mart (no one bigger!)– Sells 10 B items per year
– 100 bytes/item => 1 TB
• ATT – 300 M calls per day (peak day)
– 10 B calls per year
– 100 b/call = 1 TB
8
VLDB Reality Test• Its HARD to find 1 TB of
transaction data– 100 M web hits/day
– 250 B/hit
– 1TB/year
• Its HARD to find 1TB of text data– 100 M web pages
– 10 KB/page
– = 1 TB
• How do they do it?
• Lots of indices?– No: that is only 3x
• Precomputed Aggregates?– Yes: OLAP benchmark
• Start at 30 MB
• Use 2.7 GB or 6GB database
– But: this is dumb
• Email?– Microsoft: 6 TB
– Hotmail: 3.5 TB
– AOL?
9
Data Tidal Wave• Seagate 47GB drive @ 3k$
– 100 GB penny per MB drive coming in 2000
• 10 $/GB = 10 k$/ Terabyte! (in y2k)– Everyone can afford one
• What’s a terror bite?– If you sell ten billion items a year (e.g Wal-Mart)
– And you record 100 bytes on each one
– Then you got a Terror Bite
• Where will the terror bytes come from?– Multimedia (like the TerraServer) and...
10
Multi Media: Very Large DBs • Photo is 100 KB, not 100 B
– So, photo DBs are 1,000x larger
• Examples:– Scanned documents– Photo records of products/people/places– Surveillance– Scientific monitoring
11
Some TerrorByte Databases
• EOS/DIS (picture of planet each week)– 15 PB by 2007
• Federal Reserve Clearing house: images of checks– 15 PB by 2006 (7 year history)
• Sloan Digital Sky Survey:– 40 TB raw, 2 TB cooked
• TerraServer:
12
Scaleup - Big Database• Build a 1 TB SQL Server database
– Show off Windows NT and SQL Server scalability
– Stress test the product• Data must be
– 1 TB– Unencumbered– Interesting to everyone everywhere– And not offensive to anyone anywhere
• Loaded – 1.1 M place names from Encarta World Atlas– 1 M Sq Km from USGS (1 meter resolution)– 2 M Sq Km from Russian Space agency (2 m)
• Will be on web (world’s largest atlas)• Sell images with commerce server.• USGS CRDA: 3 TB more coming.
13
TerraServerWorld’s Largest PC!
• 324 disks (2.9 terabytes)
• 8 x 440Mhz Alpha CPUs
• 10 GB DRAM
• NT EE & SQL 7.0
• Photo of the planetUSGS and Russianimages
14
Background• Earth is 500 Tera-meters square– USA is 10 tm2
• 100 TM2 land in 70ºN to 70ºS
• We have pictures of 6% of it– 3 tsm from USGS
– 2 tsm from Russian Space Agency
• Compress 5:1 (JPEG) to 1.5 TB.
• Slice into 10 KB chunks
• Store chunks in DB
• Navigate with
– Encarta™ Atlas• globe
• gazetteer
– StreetsPlus™ in the USA
40x60 km2 jump image
20x30 km2 browse image
10x15 km2 thumbnail
1.8x1.2 km2 tile
• Someday– multi-spectral image
– of everywhere
– once a day / hour
15
USGS Digital Ortho Quads (DOQ)
• US Geologic Survey
• 3 TeraBytes• Most data not yet published• Based on a CRADA
– TerraServer makes data available.
USGS “DOQ”
1x1 meter4 TBContinentalUSNew DataComing
16
Russian Space Agency(SovInfomSputnik) SPIN-2 (Aerial Images is Worldwide Distributor)
• 1.5 Meter Geo Rectified imagery of (almost) anywhere
• Almost equal-area projection
• De-classified satellite photos (from 200 KM),
• More data coming (1 m)
• Want to sell imagery on Internet.
• Putting 2 tm2 onto TerraServer.SPIN-2
18
1TB Database Server AlphaServer 8400 4x400. 10 GB RAM 324 StorageWorks disks 10 drive tape library (STC Timber Wolf DLT7000 )
SPIN-2
Hardware
S T C9 7 4 0D L TT a p eL i b r a r y
4 89 G BD r i v e s
4 89 G BD r i v e s
4 89 G BD r i v e s
A l p h aS e r v e r8 4 0 0
E n t e r p r i s e S t o r a g e A r r a y
1 0 0 M b p sE t h e r n e t S w i t c h D S 3 I n t e r n e t
M a pS e r v e r
4 89 G BD r i v e s
4 89 G BD r i v e s
4 89 G BD r i v e s
8 x 4 4 0 M H zA l p h a c p u s1 0 G B D R A M
4 89 G BD r i v e s
S i t eS e r v e r s
19
broswer
HTMLJava
Viewer
The Internet
Web Client
Microsoft AutomapActiveX Server
Internet InfoServer 4.0
Image DeliveryApplication
SQL Server7
MicrosoftSite Server EE
Internet InformationServer 4.0
Image Provider Site(s)
Terra-Server DB Automap Server
Sphinx(SQL Server)
Terra-ServerStored Procedures
InternetInformationServer 4.0
ImageServer
Active Server Pages
MTS
Terra-Server Web Site
Software
20
• Backup and Recovery– STC 9717 Tape robot– Legato NetWorker™– Sphinx Backup/Restore Utility– Clocked at 80 MBps!!
• SQL Server Enterprise Mgr– DBA Maintenance– SQL Performance Monitor
System Management &
Maintenance
21
TerraServer File Group Layout• Convert 324 disks to 28 RAID5 sets
plus 28 spare drives
• Make 4 NT volumes (RAID 50) 595 GB per volume
• Build 30 20GB files on each volume• DB is File Group of 120 files
HSZ70 A
HSZ70 B
HSZ70 A
HSZ70 B
HSZ70 A
HSZ70 B
HSZ70 A
HSZ70 B
HSZ70 A
HSZ70 B
HSZ70 A
HSZ70 B
E: F: G: H:
HSZ70 A
HSZ70 B
22
AlternateNameName
CountryIDStateIDTypeID
GazSourcIDLatitude
LongitudeUGridIDZGridIDDOQdate
SPIN2date
PlaceID
Place
ImageFlag
FeatureType
TypeIDDescription
13
GazetteerSource
GazSrcIDDescription
11,089,897
Country
CountryIDCountryName
UNcode
264
State
StateIDCountryIDStateName
1083
CountrySearch
AlternateNameCountryIDGazSrcID
1148
StateSerach
AlternateNameCountryID
StateIDFreatureIDGazSrcID
3776
PlaceGrid
ZGridIDBestPlaceName
XDistanceYDistrance
50,000,000
Gazetteer Design
• Classic Snowflake Schema
• Fast First hint to Optimizer
23
1
ImgSource
SrcIDSrcName
SrcTblNameSrcDescription
GridSysIDImgTypeID
2
Jump
UGridIDZGridID
ZTileGridIDImgDataImgDate
ImgTypeIDImgMetaID
SrcIDEncryptKeyFile Name
.65 M SPIN21.5 M USGS
OriginalMetaData
OrigMetaIDSrcID
ImageSourceAgency
SourcePhotoIDSourcePhotoDateSourceDEMDate
MetaDataDateProductionSystem
ProductionDateDataFileSizeCompressionHeaderBytes
…80 other fields
650 k SPIN22 M USGS
Pick
NameDescription
LinkPickDate
10
ImageMeta
ImgMetaIDOrigMetaIDImgStatusImgDate
ImgTypeIDJumpPixHeightJumpPixWidth
BrowsePixHeightBrowsePixWidthThumbPixWidthThumbPixHeight
CutColCutRowMidLat
MidLongNELat
NELongNWLat
NWLongSELat
SELongSWLat
SWLongUGridID
UTMZoneXUtmIDYUtmIDXGridIDYGridIDZGridID
650 k SPIN22 M USGS
ImgType
ImgTypeIDImgFileDescImgFileExt
MimeStr
4
Browse
UGridIDZGridID
ZTileGridIDImgDataImgDate
ImgTypeIDImgMetaID
SrcIDEncryptKeyFile Name
.65 M SPIN21.5 M USGS
Thumb
UGridIDZGridID
ZTileGridIDImgDataImgDate
ImgTypeIDImgMetaID
SrcIDEncryptKeyFile Name
.65 M SPIN21.5 M USGS
Tile
UGridIDZGridID
ZTileGridIDImgDataImgDate
ImgTypeIDImgMetaID
SrcIDEncryptKeyFile Name
16 M SPIN296 M USGS
xxx
UGridHits
URLUGridID
ZTileGridIDcount
Log
URLTime
<extensivelist of actionparameters
xxx
TileMeta
ImgMetaIDOrigMetaID
SrcIDImgStatusImgDate
ImgTypeIDTilePixHeightTilePixWidth
CutColCutRowMidLat
MidLongNELat
NELongNWLat
NWLongSELat
SELongSWLat
SWLongUGridID
UTMZoneXUtmIDYUtmIDXGridIDYGridIDZGridID
16 M SPIN296 M USGS
Image Data Design• Image pyramid stored in DBMS (250 M recs)
24
Image Delivery and LoadDLTTape “tar”
\Drop’N’ DoJobWait 4LoadLoadMgr
DB
100mbitEtherSwitch
108 9.1 GBDrives
Enterprise Storage Array
AlphaServer8400
108 9.1 GBDrives
108 9.1 GBDrives
STCDLTTape
Library
604.3 GBDrives
AlphaServer4100
ESAAlphaServer4100
LoadMgr
DLTTape
NTBackup
ImgCutter
\Drop’N’ \Images
10: ImgCutter20: Partition30: ThumbImg40: BrowseImg45: JumpImg50: TileImg55: Meta Data60: Tile Meta70: Img Meta80: Update Place
...LoadMgr
25
SQL 7 Testimonial• We started using it March 4 1997
– SQL 7 Pre-Alpha
– SQL 7 Alpha
– SLQ 7 Beta 1
– SQL 7 Beta
• Loaded the DB twice– (we made application mistakes)
• Now doing it “right”
• Reliability: Great! SQL 7 never lost data
• Ease of use: Great!
• Functionality: Great!
26
Outline
• Status report on Commodity Server Performance
• Why Most VLDBs will be Multi-Media Servers
• Preview of Microsoft’s SQL Server 7
27
SQL 7: Easy & Functional
EasyEasy Dynamic self managementDynamic self management Multi-site managementMulti-site management Alert/response managementAlert/response management Job scheduling and executionJob scheduling and execution Scriptable managementScriptable management profiling/tuning toolsprofiling/tuning tools Fully UnicodeFully Unicode English Language QueryEnglish Language Query Integrated text search engineIntegrated text search engine
ScalabilityScalability
Data WarehousingData Warehousing
28
Made It Easier!(fewer knobs)
• Desktop & Workgroups– Auto Configure Engine / Dynamic Disk/memory
– Reduce Learning Curve, Increase Productivity
– Self-Managing SQLAgent, Wizards, “Task Pads”
• Large Organizations– Deploy/manage hundreds of SQL Servers
– Lower TOC for Large Environments
– Multi-Server Operations/ “Lights-out” Environment
29
• Admin servers from one place• Automate simple stuff• Wizards for common stuff• Manage arrays of servers– operations, security,…
– Replication
– Import/export
•Interface is scriptable– COM object model
– Script with Java, VB, ...
•Scheduling and Multi-step jobs
Multi-Site Management
30
DBA and Developer Tools• Built-in GUI
– data/schema design
– data query & edit
– intgrated with programming tools
• SQL Server Profiler– Selected server events and trace criteria
– “Capture” output to screen or replay
• SQL Server Expert– Analyzes actual server usage history
– Makes recommendations to improve performance
– Recommends Index design
– Recommends operations procedures
31
Wizards and GUIs• Wizards galore (over 50 at last count)• MS Access as a query interface• Built-in data access tools (integrated with tools)• Graphical show plan
32
Many New Wizards...
• Create a Database
• Scheduled Backup
• Create a Maintenance Plan
• Create a Scheduled Job
• Create an Alert
• Security Wizard
• Import Data to SQL Server
• Export Data From SQL Server
• Clustering (Wolfpack)
• Index Tuning Wizard
Web Assistant Register Servers Configure Replication Create Publication Create Pull Subscription Create Push Subscription Replication Partitioning Create an Index Create a Stored Procedure Create a View More to come...
33
Distributed Management Objects (SQL-DMO)
• COM Interfaces for administering SQL Server– Embedded Administration (no UI)
• All Administration Functions Supported– Server, Database Configurations, Settings– Object Creation, Security, Replication, Scripting,..– 40+ Objects, 1000+ properties and methods
• Integration Interface for ISV Administration– I.e., Baan using DMO for Scripted App Install
• Scripting Via VBA and Jscript + DCOM
34
DMO: Object Model (Overview)
Users
Databases
Logins
DB Options
Configurations
Alerts
Operators
Tasks
Jobs
SQLAgent
Transaction Logs
Publications
Remote Login
Linked ServersColumns
IndexesView
Stored Procs
Table
Files
FileGroups
Keys (PK/FK)
TriggersRules
Defaults
SQL Server
35
DMO Scripting
• Backup a Database
Set MyServer = CreateObject("SQLDMO.SQLServer")‘Create Server ObjectSet MyBackup = CreateObject("SQLDMO.Backup") ‘Create Backup Object
MyServer.Name = “MSSALES” ‘ Identify ServerMyServer.LoginSecure = True ‘ Windows NT AuthMyServer.Connect ‘ Connect
MyBackup.Database = ”SALESII” ‘ Database to backupMyBackup.Files = "\\MyServer\Backups\" _ ‘ Backup Location
+ MyBackup.Database +”.bak” ‘ Name Backup FileMyBackup.SQLBackup MyServer ‘ Back it Up
MyServer.Disconnect ‘ We’re Done!
36
Scalability
Win9x/NTW versionWin9x/NTW version Dynamic row-level lockingDynamic row-level locking Improved query optimizerImproved query optimizer Intra-query parallelismIntra-query parallelism 64-bit support64-bit support ReplicationReplication Distributed queryDistributed query High Availability ClustersHigh Availability Clusters
EasyEasy
ScalabilityScalability
Data WarehousingData Warehousing
37
Scale Down to Windows 95-98• Full function (same as NTW)
• Self managing
• Many tools
• Integration with Next MS Access
• Great for imbedded apps
38
Replication• Transactional and Merge
• Remote update
• ODBC and OLE DB subscribers
• Wizards
• Performance
2PC, 2PC, RPCRPC
SubscriberSubscriber
DB2
CICS SubscriberSubscriberSubscriberSubscriber
VSAM
OS 390DB2
PublisherPublisher
Updating SubscriberUpdating Subscriber(immediate updates)(immediate updates)
DistributorDistributor
SubscriberSubscriber
39
•# of emp. per group# of emp. per group
•total inc. per grouptotal inc. per group
Local Agg.Local Agg.
4 x 50 rows4 x 50 rows
+ + + +
DisksDisks50,000 rows50,000 rows
Global Agg.Global Agg. Result 50 rowsResult 50 rows+
Parallel QuerySMP & Disk Parallelism
• Plus Distributed• Plus Hash Join (fanciest on the planet)
• Plus Optimized Partitioned views
40
Distributed Heterogeneous QueriesData Fusion / Integration
Join spread sheets, databases, directories,
Text DBs
etc.
Any source that exposes OLE DB interfaces
SQL Server as gateway, even on the desktop
DatabaseDatabase(DB2, VSAM, Oracle, …)(DB2, VSAM, Oracle, …)
SpreadsheetSpreadsheet
PhotosPhotos
MailMail
MapsMaps
DocumentsDocumentsand the Weband the Web
DirectoryDirectoryServiceService
SQL 7.0Query
Processor
41
UtilitiesThe Key to LARGE Databases
• Backup– Fuzzy– Parallel– Incremental– Restartable
• Recovery– Fast– File granularity
• Reorganize– shrinks file – reclusters file
• Auto-repair
42
Data Warehousing
Warehousing FrameworkWarehousing Framework Visual data modelerVisual data modeler Microsoft repositoryMicrosoft repository Data transformation services Data transformation services
(DTS)(DTS) Plato & Dcube - Multi Plato & Dcube - Multi
Dimensional Data CubesDimensional Data Cubes English query 2.0English query 2.0 Built-in text-index engineBuilt-in text-index engine
EasyEasy
ScalabilityScalability
Data WarehousingData Warehousing
43
Key Microsoft Data Warehouse Programs
• Data Warehouse Framework (DWF)– Process -- for building, using and managing– Pipeline -- for metadata flow– Protocols -- to integrate components
• Data Warehouse Alliance (DWA)– Partners -- ISVs pledged to the framework and its parts– Products -- complete spectrum from Microsoft and
third-parties
44
Microsoft Data Warehousing Framework
OperationalData
(OLE-DB **)
OperationalData
(OLE-DB **)
Data Warehouse Design(logical/physical schema*/ data flow**)
Data Warehouse Design(logical/physical schema*/ data flow**) End-User Tools
(Excel**,Access,
English Query)
End-User Tools
(Excel**,Access,
English Query)
Data Warehouse Management(Console*, Scheduling**, Events**,Topology*,)
Data Warehouse Management(Console*, Scheduling**, Events**,Topology*,)
Data Transformations
(DTS**)
Data Transformations
(DTS**)
Data Marts(SQL Server** &OLAP Server**)
Data Marts(SQL Server** &OLAP Server**)
OLE
-DB
**O
LE-D
B**
Building Using
Man
ag
ing
** available in SQL Server 7 (* partially) Meta-Data FlowData Flow
Microsoft Repository** (Persistent Shared Meta-Data)Microsoft Repository** (Persistent Shared Meta-Data)
DB Schema**DB Schema** Transformation**Transformation** Scheduling Scheduling OLAPOLAP
Data Mart Design**(Cubes/Star schema)
Data Mart Design**(Cubes/Star schema)
45
Alliance for Data Warehousing
BMCData MirrorExecusoftInformaticaMicrosoftPlatinum TechnologyPraxisPrismSagentSASSterlingV-Mark
AndyneBusiness ObjectsCognosIQ SoftwareMicrosoftNCR Data MiningPilotPlatinum TechnologySagentSASSeagateWall Data
DW Build DW Access
Technical and marketing relationship
Supports SQL Server storage engine
Third-party products tested with BackOffice
46
DW Alliance Milestones
• 9/96 - Launched with 8 founding members
• 3/97 - Design review
• 1/97 - 6/97 - Expanded to 21 members
• 7/97 - Repository design review – Team development of shared metadata
• 9/97 - OLE DB for OLAP API specification
• 1H’98 - Integration development with Sphinx DTS and Replication APIs
47
Microsoft Repository• Based on joint Sterling/Microsoft design (Shipped 97Q2)• Wide distribution:VB, Visual Studio and Third-Parties• Designed with over 60 vendors• Extended to support DB schema, transformations, OLAP
– Key element of the DW Framework
• UML is abstract model• Everything viewable
in UML terms
UML Unified Modeling Language
UMX Uml Extensions
CDE Component Descriptions
COM Component Object Model
DBM Database Model
DTM Data Type Model
GEN Generic
SQL Microsoft SQL Server
OCL Oracle
UML
UMX
CDE
COM
DBMDTM GEN
SQL OCL
48
Repository & Data Warehousing
• Common infrastructure -- the meta-data pipeline
• Supports interoperability between data warehousing tools and products
• Process:– Initial spec developed with 12 vendors– Gathering feedback now– Final spec review in Redmond, 2/98
49
Data Transformation
RepositoryRepositoryMetadataMetadata
TransformsTransforms Oracle > SQL ServerOracle > SQL Server
Function Example() Transform()
If DTSSource(“CreditRating”) = “1” thenDTSDestination(” Risk ") = ”Good"
Else If DTSSource(”Credit") = ”2”DTSDestination(” Risk ") = ”Average”
Else If DTSSource(”Credit") = ”3”DTSDestination(” Risk ") = ”Bad”
ElseExample = DTS_SkipRow
End if
End Function
TransformationTransformationObjectsObjects
ActiveX ScriptsActiveX Scripts
SQLAgentSQLAgentMultiserverMultiserverOperationsOperations
Data PumpData PumpData PumpData Pump
IDTSDataPumpIDTSDataPump IUnknownIUnknown
• Workflow system manages Data Pump– Pre-defined transforms using the DTS GUI– Procedural VB Script, JavaScript, VBA, any COM
• Multi-stream in, Multi-stream out
50
Transformations• Data quality and validation
– Missing values, scrubbing, exception handling
• Data integration– Heterogeneous query, join keys, elim. dups
• Transforms– Combine/decompose multiple columns to one
• Aggregation
• Central metadata– Business rules, data lineage
51
Flexible Architecture• Debates between
MOLAP and ROLAP vendors obscure customer needs
• Plato is the product that best supports MOLAP, ROLAP and Hybrid and offers the most seamless integration of all three
• Users & apps only see cubes
MO
LAP
UserView
Dataload
PersistentStore
UserView
Dataaccess
MDCache
RO
LAP
UserView
MDCache
Hyb
rid
52
Source tableSource table
Partition 1Partition 1
ROLAP
Partition 2Partition 2
Partition 3Partition 3
ROLAP
EuropeEurope
USAUSA
AsiaAsia
MD SQLMD SQL
SQLSQL
Plato and Dcubeand HOLAP
““Plato”Plato” serverserver
““Plato”Plato”
DesignerDesigner
Dcu
be
Dcu
be
ClientClientappapp
User 1User 1
Dcu
be
Dcu
be
ClientClientappapp
User 2User 2
CHEVY
FORD 19901991
19921993
REDWHITEBLUE
By Color
By Make & Year
By Color & Year
By MakeBy Year
Sum
53
How Plato Handles Data Explosion
Fact Table
Quarter
Product Family
Quarter
ProductMonth
Product Family
Month
Products
Aggregation Wizard finds the aggregations that feed the most other aggregations
54
How Plato Handles Data Explosion
• Aggregation Wizard finds the “80-20” rule in the data– The 20 percent of all possible pre-aggregations that provide 80 percent of
the performance gain
– Analyses level counts for each dimensions and parent-child ratios for each level
• Independent of OLAP data model
55
OLE DB For OLAP
• OLE DB extensions to access MD data – Part of OLE DB 2.0
• One new object: Dataset
• Enhancements to existing objects
• Heavily leverages OLE DB
56
OLE DB For OLAPObjects And Interfaces
CommandCommand CoCreateInstanceCoCreateInstance
EnumeratorEnumerator
Data sourceData source
SessionSession
Schema RowsetsSchema Rowsets
Flattened RowsetFlattened Rowset
Range RowsetRange Rowset
DatasetDataset
57
English Query
58
OBJECT RELATIONALThe Next Great DBMS Wave
• All the DB vendors are adding objects
• Microsoft is adding DBs to Objects
• Integration with COM+
• Gives user-defined types and objects
• Plug-ins will be Billion dollar industry– Blades for SQL Server razor
59
Outline
• Status report on Commodity Server Performance
• Why Most VLDBs will be Multi-Media Servers
• Preview of Microsoft’s SQL Server 7
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