1. Oracle - Engineered for Innovation
Thomas Kyte

2. “A Relational Model for Large Shared Databanks”
The Beginning...
Data Model with Structure
Data Independent of Code
Set-oriented
1977 the work begins
“A Relational Model for Large Shared Databanks”
It started with one profound idea
In 1970 E.F. Codd wrote the book….the mathematical model that would define the future of RDMBS.
He later hooked up with C.J. Date of IBM and Codd and Date would become known as father and grandfather of relational theory.
Codd and Date became mythical figures dispensing truths about the purity of various implementations of RDBMs. Had 12 rules of relational databases.
Data Model with Structure, Integrity Rules, Operations
Data Defined Independently of Programs
Set-oriented, Declarative Language
E.F. Codd

3. GPS 1978 No one thought it could be done
It wouldn’t be fast enough, no one would buy it
The early adopters came to us.
First test outperformed Cullinet’s DBMS – immediately realized this was a break-through, and the company would be worth 100’s of millions
The FIRST Commercial SQL RDBMS
An Impressive First SQL
Non-procedural power (joins, subqueries) for ad hoc access
A single language for data definition, control, access
Unique Oracle extensions: outer join, CONNECT BY
A Simple Server
No transactions – like MySQL
Limited reliability
Portability from the Start – driven by customer requirements from the beginning.
Digital PDP-11 operating systems: RSX, RSTS, IAS, Unix
DEC VAX (compatibility mode)

4. First RDBMS: Version 2 June 1979
FIRST Commercial SQL RDBMS
Impressive First SQL
Joins, Subqueries
Outer Joins, Connect By
A Simple Server
No transactions, ‘Limited’ Reliability
Portability from the Start
Written in Fortran
But multi-platform – PDP11, Dec VAX
No one thought it could be done
It wouldn’t be fast enough, no one would buy it
The early adopters came to us.
First test outperformed Cullinet’s DBMS – immediately realized this was a break-through, and the company would be worth 100’s of millions
The FIRST Commercial SQL RDBMS
An Impressive First SQL
Non-procedural power (joins, subqueries) for ad hoc access
A single language for data definition, control, access
Unique Oracle extensions: outer join, CONNECT BY
A Simple Server
No transactions – like MySQL
Limited reliability
Portability from the Start – driven by customer requirements from the beginning.
Digital PDP-11 operating systems: RSX, RSTS, IAS, Unix
DEC VAX (compatibility mode)

5. IBM model number 5150, introduced on August 12, 1981.
IBM PC – 1981
IBM model number 5150, introduced on August 12, 1981.

6. Internet (as we know it) – 1983
The first TCP/IP-based wide-area network was operational by January 1, 1983 when all hosts on the ARPANET were switched over from the older NCP protocols.

7. Portability: Version 3 March 1983
New Implementation Designed for Portability
Written in ‘C’
Single Source
Architectural Changes
Transactions, multi-versioning, no read consistency
AI/BI files
Oracle Corporation – name established
Innovation – “C” code was portable, leading edge and the future of the day – Ken Jacobs – why did we decide on C?
And it was as practical as it was “visionary” b/c we had 2 customers on 3 different os – efficiency of development
Oracle Corp name established to align product and company
Definition: the source of wisdom, a person who sees the future – prophetic for the visionary approach
New Implementation Designed for Portability
All code written in C
Architectural Changes
Transactions, but no read consistency
Oracle Corporation – name established
Selling the idea of Relational Database
Meanwhile, what was going on at IBM?
Didn’t want to undercut IMS – IMS loyalists fought to keep relational from being released – until SQL/DS on
(second biggest mistake in the history of Software)
Ask, what was the biggest mistake?
Biggest mistake in software history was giving the PC Operating System to Microsoft
Spent the majority of our time selling the idea that RDBMS could be commercially viable
The biggest mistake IBM would make in the history of Software was outsourcing the development of MS DOS to MSFT
2nd biggest mistake CLINGING to the present, status quo, SQL/DS – not embracing the RDBMS early on
Lack of vision, conservative business values, not risk takers
“IBM could have had the all of the relational database Market if they’d been more aggressive”
“I don’t know of any place or any time where there aren’t great possibilities”
At about the same time Xerox Corporation was doing something similar for a local entrepreneur(Steve Jobs) who visited them in Palo Alto Research Center
Steve Jobs, Apple – the UI
Larry Ellison, Oracle – the RDBMS
Bill Gates, MSFT – the MS DOS o/s
IBM close to collapse

10. Cooperative Server: Version 5 April 1985
My First Oracle Experience
1st Client/Server
Cooperative Server
Distributed Processing
Parallel Server
Portability
V5 was first to go beyond 640K memory on PCs
Single-user for Macintosh o/s
SQL_TRACE
select trace('sql',1),1 from dual;
Client Server is born
Love/hate with Bill Gates, and Microsoft – “Microsoft does not suffer from the not-invented-here syndrome”
Oracle releases Early parallel server, precursor to today’s RAC
MS-DOS, GUI was MAC, Browser was Netscape,…Innovative choices
IBM releases DB2 for MVS – 6 years late on their own research paper
Martin Pickard, recent hire form MIT, wrote SQL*PME, Protected Mode Executive, to extend beyond the 640K memory boundary, b/c no one told him he couldn’t
Innovation!
Selling points – NOW 3 Cs and a P
Compatibility with Industry Standards
Connectibility to heterogeneous DBs(V5)
Capability robust, fast, fully functional DB(aka Reliability)
And
Portability
1st Client/Server
SQL*Net
Cooperative Server
Distributed Process, SQL*Connect
Parallel Server
V5 was first to go beyond 640K memory on PCs
Single-user Oracle released for Macintosh o/s
Portability , Compatibility, Capability, Connectability
IBM – DB2 is released for MVS

11. Transaction Processing: Version 6 July 1988
New Architecture
Performance (first SMP)
Availability
TPO
PL/SQL
V6 Lays Architectural Groundwork for the Future
This was a rewrite of the entire database fundamentally
Larry took a HUGE RISK and decided to do a complete rewrite and redesign of the DB form the bottom up
** Had he not taken that RISK and done that INNOVATION, I doubt we'd have won the rdbms game. 3 years of development investment- similar to Project Fusion.
He hired many MIT and other grads from top schools in what would become known as the class of 1986.
It was this redesign that allowed us to blow away Sybase and be the Scalable db for the next 20 years.
First Commercial level Parallel Server (precursor to RAC) that allowed us to win the TPC BM # going forward
Bench Marking was the name of the game
Shut off the Oxygen Campaigns against Sybase and Ingres and Kill Informix Campaigns followed and we defeated all of our RDBMS competitors
With Speed, scalability and robustness.

12. World Wide Web – 1990’ish
The World Wide Web was created in 1989 by British scientist Tim Berners-Lee, working at the European Organization for Nuclear Research (CERN) in Geneva, Switzerland, and released in 1992.

13. Oracle7.3 February 1996 Partitioned Views Bitmapped Indexes
Asynchronous read ahead for table scans
Standby Database
Deferred transaction recovery on instance startup
Updatable Join View
SQLDBA no longer shipped.
Index rebuilds
DBV introduced
Context Option
PL/SQL - UTL_FILE
Spatial Data Option
Tablespaces changes - Coalesce, Temporary Permanent,
Trigger compilation, debug
Unlimited extents on STORAGE clause.
Some init.ora parameters modifiable - TIMED_STATISTICS
HASH Joins, Antijoins
Histograms
Oracle Trace
Advanced Replication Object Groups

16. Data Warehouses Growing Rapidly Tripling In Size Every Two Years
Size of the Largest Data Warehouses
200
400
600
800
1000
1998
2000
2002
2004
2006
2008
2010
2012
Terabytes of Data
Source: Winter TopTen Survey, Winter Corporation, Waltham MA, 2008.

17. Enabling the Private Database Cloud Years of continuous Oracle innovation
Oracle Exadata
Smart Scans
Smart Flash Cache
Oracle Database 11g
Hybrid Columnar Compression
InfiniBand support
Quality of Service Management
Server Pools
Oracle Database 10g
I/O resource management
Instance caging mt
Automatic Storage Management
Dynamic Database Services
Real Application Clusters
Database Services
Oracle9i Database
CPU Resource Management
© 2011 Oracle Corporation

18. Three Major Database Focus Areas Engineered for Innovation
SOCIAL
BLOG
SMART METER
CLOUD COMPUTING PRIVATE AND PUBLIC
ENGINEERED SYSTEMS
BIG DATA

19. Building Managed Server and Storage Pools Real Application Clusters
Automatic Storage Management
Enterprise Manager
Real Application Clusters mt
In-Memory Database Cache 19

20. Service Level Management Resource Manager and Instance Caging
Resource Manager allocates CPU and Memory
Instance caging allocates cores per instance
Capacity-on-demand for elastic cloud computing

21. Network SQL Monitoring and Blocking
Complete Data Security Firewall, Encryption, Separation of Duty and Monitoring
Encrypted
Database
Data
Masking
Activity Audit
Network SQL Monitoring and Blocking
Data Discovery
Applications
Compliance Scan
Most companies have implemented the 3 As at some level: Authentication, Authorization, auditing. Some still use generic shared accounts, which while convenient cannot be used to track the actual user who made the change. Some still grant overly excessive privileges instead of going through the exercise of least privileges. This can be very dangerous as any SQL injection attack or stealing of pwd can be disastrous. In the end you want to audit your privilege users, but unless you monitor the audit logs, auditing may not be much of a deterrent.
A small percentage of the companies do patching.
This means that most others are very vulnerable to attacks discussed in previous slides. We recommend that in addition to 3 As and patching, you seriously consider the following:
A database firewall to reduce the threats from the web users. The firewall can understand the SQL coming through the wire, analyzing it, and then determining whether it should be allowed to go the database. The firewall should also be able to both monitor and block unauthorized traffic including SQL injection attacks.
Encrypt the database data to reduce the threats from the OS administrator or any other software running on the database machine. As the data gets backed up, you may want to encrypt the backup to reduce threats from inadvertent losses or theft of the tapes. You also want to encrypt the traffic to reduce the risk of someone sniffing the wire. Finally, to reduce the threats from your test or dev teams, you want to mask the data before you give it to them.
The other threat that you want to handle is the threat from the DBA or hackers with DBA password credentials. You want the DBAs to do the job of tuning and managing the system, but you do not want them to view or modify your sensitive data. You also want to ensure that even if someone has the DBA password, they meet other factors before they are given access to the database.
Now at the end of the day, you have to allow your privileged users to do their jobs. And of course you trust them, but by auditing their activities throughout the enterprise you can implement “trust but verify” principle. You may want to collect audit data from throughout your enterprise, analyze the data, raise alerts if needed, and then create reports for your auditors.
Vulnerability Scan
Patch Automation
Unauthorized DBA Activity
Multi-factor authorization

22. Create Reference Configuration Provision Database on Cloud
Provisioning Software to the Cloud Lower complexity via Reference Configurations
Gold image reference configurations
Standardized deployments via profiles
Rapidly provision databases to the Cloud
Monitor change centrally to ensure compliance
Create Reference Configuration
Provision Database on Cloud
Stage as Gold Image
Manage Centrally

23. Metering and Chargeback Enterprise Manager 12c
Resource usage metering
Historical usage trends
Cost allocation and charge plan evaluation
Reporting for cloud self- service application 25 50
100
Number of servers
Number of CPUs
Memory
Local Storage (GB)
$100K
Discover & Plan
Track Usage
Charge User

24. Optimized, Pre-Integrated Cloud Platform Oracle Exadata Database Machine
Database Server Pool
Oracle Database 11g Release 2
Oracle Real Application Clusters
Automatic Storage Management
Storage Server Pool
Up to 336 TB disk
5 TB flash storage
Oracle Exadata Storage Software
InfiniBand Network
40 Gb/sec redundant switches

25. Improve Data Warehouse performance 10x Exadata Smart Scans
Select sum(sales) where salesdate= ‘21-Sep-2010’…
Sum
Filter Sales for Sep
What Were Yesterday’s Sales?
Data intensive processing runs in Exadata Storage Servers
Rows and columns filtered as data streams from disks

26. Storage Optimization Next Generation Compression Technology
Up to
OLTP
Compression
Increase compression as data ages
Improve query performance for table scans
Improve cache density for OLTP performance
No changes to existing applications
Cascade storage savings throughout data center
Up to
50X
Hybrid Columnar
Compression (Exadata, Pillar Axion, Sun ZFS Storage Appliance)

27. Extreme Performance for OLTP Exadata Smart Flash Cache
Full rack has 5 TB of Smart Flash Cache
Can process over 1 million IOs per second

28. Public Cloud Oracle Public Cloud (cloud.oracle.com)
Self Service
Monthly Subscription
Simple Pricing
Services
Application
Platform
Platform Services
Java Cloud Service
Database Cloud Service

29. Database Applications in the Public Cloud Database Cloud Access and Applications
Oracle Application Express
Applications
RESTful Web Services
SQL Developer
Oracle Java Cloud

30. Big Data Buzz
“Ten reasons why Big Data will change the travel industry”
“The challenge– and opportunity– of big data”
“Why big data is a big deal”
InfoWorld – 9/1/11
McKinsey Quarterly—5/11
Tnooz -8/15/11
“Keeping Afloat in a Sea of 'Big Data”
“Getting a Handle on Big Data with Hadoop”
“The promise of Big Data”
ITBusinessEdge – 9/6/11
Businessweek-9/7/11
Intelligent Utility-8/28/11

31. Big Data Use Cases Today’s Challenge New Data What’s Possible
Healthcare Expensive office visits
Remote patient monitoring
Preventive care, reduced hospitalization
Manufacturing In-person support
Product sensors
Automated diagnosis, support
Location-Based Services Based on home zip code
Real time location data
Geo-advertising, traffic, local search
Public Sector Standardized services
Citizen surveys
Tailored services, cost reductions
Retail One size fits all marketing
Social media
Sentiment analysis segmentation

32. What Makes it Big Data? VOLUME VELOCITY VARIETY VALUE
SOCIAL
BLOG
SMART METER
VOLUME
VELOCITY
VARIETY
VALUE

35. Make Better Decisions Using Big Data Big Data in Action DECIDE ACQUIRE
ANALYZE
ORGANIZE

36. Acquire all available data
Big Data in Action
DECIDE
ACQUIRE
Acquire all available data
ANALYZE
ORGANIZE

37. Oracle NoSQL Database … Key value pair database Dynamic data model
Nodes
East
West
Central
NoSQL Driver
Application …
Read
Delete
Update
Key value pair database
Dynamic data model
Highly scalable, available
Transparent load balancing
Built using BerkeleyDB

38. Organize and distill big data using massive parallelism
Big Data in Action
DECIDE
ACQUIRE
Organize and distill big data using massive parallelism
ANALYZE
ORGANIZE

39. Analysis Sandbox Provides analysis workspace
Controlled access to resources and data
Doesn’t impact production system

40. Oracle Loader for Hadoop
Input 1
MAP
Shuffle /Sort
MAP
Shuffle /Sort
MAP
Reduce
Reduce
MAP
Shuffle /Sort
MAP
Reduce
MAP
Reduce
MAP
Reduce
Reduce
Reduce
MAP
MAP
MAP
Shuffle /Sort
MAP
Reduce
MAP
Reduce
MAP
Shuffle /Sort
Reduce
MAP
MAP
MAP
Reduce
MAP
MAP
Reduce
Input 2

41. Analyze all your data, at once
Big Data in Action
ANALYZE
DECIDE
ACQUIRE
Analyze all your data, at once
ANALYZE
ORGANIZE

42. R Statistical Programming Language
Open source language and environment
Used for statistical computing and graphics
Strength in easily producing publication-quality graphs
Highly extensible

43. Decide based on real-time big data
Big Data in Action
DECIDE
ACQUIRE
Decide based on real-time big data
ANALYZE
ORGANIZE

44. Dashboard Analytics Oracle Business Intelligence Enterprise Edition
Advanced dashboard visualization
Runs BI and EPM applications
Integrating R Analytics
Embed R script’s web interface in BI dashboard
Graphics will stream to BI dashboard

45. Oracle Integrated Solution Stack for Big Data
ACQUIRE
Oracle NoSQL
Database
HDFS
Enterprise
Applications
ORGANIZE
Hadoop (MapReduce)
Oracle Loader for Hadoop
Oracle Data Integrator
ANALYZE
In-Database Analytics
Data
Warehouse
DECIDE
Analytic Applications

46. Oracle Exalytics Hardware
Engineered for extreme analytics
40 Intel processor cores
1 Terabyte main memory
40 Gb InfiniBand connection to Oracle Exadata

47. Oracle Exalytics Software
Oracle TimesTen In-Memory Database
Adaptive in-memory caching of analytics
In-memory columnar compression
Tightly integrated with Oracle Exadata
Enables speed-of-thought visualization
Oracle Business Intelligence Foundation Suite

48. Oracle Big Data Appliance Hardware
18 Sun X4270 M2 Servers
48 GB memory per node = 864 GB memory
12 Intel cores per node = 216 cores
24 TB storage per node = 432 TB storage
40 Gb p/sec InfiniBand
10 Gb p/sec Ethernet

49. Oracle Big Data Appliance Software
Oracle Linux
Java Hotspot VM
Apache Hadoop Distribution
R Distribution
Oracle NoSQL Database
Oracle Data Integrator for Hadoop
Oracle Loader for Hadoop

50. Oracle Strategy Engineered for Innovation
Complete Stack
Best-of-breed
Open
Vertical Integration
Extreme Performance
Engineered Systems
Complete Customer Choice
On-premise
Private Cloud
Public Cloud
Hybrid Cloud