All Data @ #OracleDigital 8 November 2016

1. ALL DATA

2. CHRISTIAN BILIEN
HEAD OF GLOBAL DATA INFRASTRUCTURE
AT SOCIÉTÉ GÉNÉRALE
RDBMS/BIG DATA/CACHE
@CBILIEN

3. THE DBA IS DEAD (AGAIN)
REALLY ?

4. Agility
Open Source
Data base as
a Service
Hadoop
Cloud
Data everywhere
Containers

5. THE JURASSIC PARK SCENARIO

6. Modern data services
(for modern DBAs)
•Automated
•Self-Serviced
•Controlled delegation
•Agile data provisioning
•Consolidated
•Faultless

7. Cloud
•THE enabler
•Cloud For DBs
=
DBaaS
⊂
PaaS

8. Monitoring
Metrics
What’s new ? (perhaps)
Metrics

9. http://www.scarydba.com/
Security
Design &
maintain
DB Ops
Automation
DB design

10. DEMO

11. The mating of Hadoop
and Datawarehouses

12. Billions users
Hundred of millions
users
Millions users
Next generation databases

13. Merv Adrian (@merv) tweeted at 7:46
PM on Thur. Feb 11, 2016 :
In conversations w clients, we
repeatedly find that Hadoop
and Spark are overlapping
extensions of, not replacements
for, existing function. Gartner. Magic Quadrant for Data Warehouse
and Data Management Solutions for Analytics

14. “Data warehouse and
Hadoop are going to
completely merge.
Hadoop will look like
the data warehouse
market”
“NoSQL will
look like the
SQL market”
“They will move to
higher-level
languages,
and the only game
in town is SQL”

15. Yahoo 455 PB / 32500 nodes (2014)
Twitter 300+ PB, Multiple 1000+ machine clusters (2015)
Facebook 105 terabytes every 30 minutes (2012)
The misunderstood
Hadoop for mere mortals
=
Affordability at scale

16. Hadoop for mere mortals
Scalability
€ RDBMS
Hadoop
Initially expensive
because of lack of
expertise & initial
engineering efforts
Share everything (RAC)
Expensive hard & soft (DWH appliances)

17. SQL on Hadoop tools
Access from existing applications
•Oracle Big Data SQL
•Gluent
SQL
• Cloudera Impala
• Apache Hive
• JDBC drivers (SQL developer, Toad)
• Oracle Big Data Connectors
• Spark SQL
Import/ Export
• Apache Sqoop

18. Information Lifecycle Management

19. Thank you
@CBILIEN
Twitter/ Slideshare