Transcript Slide 1

WHAT THE MARKET-LEADING DBMS
VENDORS DON’T WANT YOU TO KNOW
Disruption is gathering steam
Curt Monash

Analyst since 1981




Covered DBMS since the pre-relational days
Also analytics, search, etc.
Own firm since 1987
Publicly available research



Feed at www.monash.com/signup.html
Blogs, including www.dbms2.com
White papers and more at www.monash.com
Database diversity

Mike Stonebraker, PhD


Curt Monash, PhD



“One size doesn’t fit all”
“Horses for courses”
“Database diversity”
Mike and Curt

The world needs 9 to 11 different kinds of
data management software
Large enterprise DBMS portfolio






Principal OLTP/multipurpose DBMS
Principal OLAP DBMS
Midrange OLTP/multipurpose DBMS
Search
Legacy DBMS
Other specialty data management
Midrange OTLP/multipurpose DBMS

“Standard editions”



VAR-centric



Oracle, DB2, SQL*Server, Informix SE
Deliberately crippled
Progress OpenEdge, Intersystems Cache’
Accidentally crippled
“Open-source”

MySQL, EnterpriseDB
OLTP DBMS worries
Besides the greatest horror – data corruption
– concerns include:






License/maintenance cost
Performance/scalability
Ease of administration
Ease of programming
Reliability/uptime
Security
Three major kinds of transactions

Traditional business transactions




Simple events = sensors, logs, etc.






Orders
Employment changes
Compliance/risk monitoring
Web site clicks
Network events
Device monitoring
Vehicle monitoring
RFID
Content serving
Traditional business transactions are



Complex
Consistent in the face of complexity
Stringently industrial-strength



Real business need
Customer expectations
Compliance
Issues to consider for applications that
record complex transactions





Schema complexity (integrity)
Schema variability
Peak performance
Uptime
Security
Issues to consider for applications that
record simple events



Performance
Uptime
What happens to the data next?
Issues to consider for applications that
serve content



Which datatypes?
Scale
The alphanumeric parts
Application metrics







Peak concurrent update throughput
Query complexity and volume
Transaction (and constraint!) complexity
Overall database size (and change!)
Uptime requirements
Security/compliance requirements
Datatype needs
And how will those evolve?
Business model changes 
Functional changes
Environmental considerations






Hardware (SMP, blade, toy collection)
Middle tier
DBMS expertise (and where it sits in the
organization)
Database administration tools
Development tools
Fixed-point applications (and how good is
their generic JDBC/ODBC support?)
And how will THOSE evolve?


Consolidation -- but what does that
mean in your shop?
Modularity
Example 1: Compliance/risk monitoring




Many feeder systems
One schema per feeder system
Accept both relational ETL and XML
Output via BI
Key requirements 1




Rigorous security
Easy administration
Eventual XML support
Unknown scalability
Example 2: Contractually-defined
products



Complex financial instruments
Vacations
Warranties
Key requirements 2





Strong native XML
Complex constraints
Availability
Security
Volume?
Example 3: Content sharing and selling


Web-facing – video, music, photo, etc.
Internal content management
Key requirements 3





Performant media datatype support
Performant order entry
Performant user tracking and
personalization
Spike scalability
24/7 availability
Major areas of OLTP DBMS
differentiation





Performance and scaling
Administration and 24/7 operation
Constraints and referential integrity
Triggers and stored procedures
Datatype support
Performance and scaling



Baseline, peak, future
For which features?
How sub-linear?
Administration and uptime



Ongoing functions – backup, security,
etc.
Indexes and mandatory maintenance??
Replication, fail-over, etc.
Database constraints


What can be done in theory?
Does it perform?
Triggers and stored procedures




Performance
Languages
Automatic generation
Development, debugging, maintenance
Datatype support




What do you need?
Performance
Datatype extensibility
(Where relevant) Quality of search
Today’s main topics





You can and should use multiple DBMS
In particular, midrange OLTP DBMS are
appealing
Not all midrange OLTP DBMS are
created equal
Both application and environmental
considerations are important
More info at www.monash.com and
www.dbms2.com