‘Dynamic schema’, what’s in it for manufacturers? This session will give you a brief overview about the process industries’ IT landscape and how the sector dealt with Big Data long before the term was even invented. We shed a quick light on the evolution of data interface standards such as OPC UA. Taking a quick look into the motivation (and ongoing struggle) for seamless real-time system integration between Control and ERP, this talk will conclude with hard facts on why MongoDB qualifies so well in the industrial solution context. Deprecating the closed-shop data silo, inmation will share first-hand experience from MongoDB-centric system development.
10. Munich
2013
Control
Typical Production Process Applications
Advanced Process Control
Mass Balancing
Laboratory Information
Management
Production Scheduling
Alarm Management
Quality Management
Operational
Excellence
Performance, Reliability, Safety
Management
ERP
Continuous Improvement
(Generic Data-Mining)
15. Munich
2013
The Spinal Cord in Production:
Contextualized Time-Series
historization of numerical data
and process events.
16. Munich
2013
The easiest way to
improve a prediction is
to add data. You can’t
infer without data. So,
store the data now and
analyze it later,…[]
Dwight Merriman, MongoDB evangelist
22. Munich
2013
You can talk
DCOM to me.
I will present you a qualified and more or
less structured namespace, consisting of
symbolically named items (tags).
Each item may have additional properties.
I can give you the actual value, the
milisecond accuracy and the value quality.
23. Munich
2013
You can talk
DCOM to me.
On request, I will constantly deliver new
Alarms & Events of any kind. Depending on
the subordinated control systems I am
connected to, the detail content of a single
event record may vary.
I can either supply all or filtered events.
24. Munich
2013
You can talk
DCOM to me.
Similar to my DA colleague on the left, I
maintain a structured namespace of tags.
Unlike this guy, I know about the entire
history of their values.
On request I will return raw values and
statistical aggregates for any period of
time.
25. Munich
2013
You can talk SOAP / XML to me.
I can do what the DA guy does, but a little
simplified.
26. Munich
2013
You can talk either binary TCP or XML to me.
I offer various options for secure communications.
I have many different profiles and facets.
(Some people are confused about me)
My smallest incarnation can work in a single chip
solution, while I’m still qualifying for an enterprise-wide
service. Obviously – Unified Architecture – I can supply
all services of those little guys in one.
28. Munich
2013
You can talk to me.
(Everybody knows that)
Very similar to the SQL language, I’m not
young of age but definitely not willing to
retire!
35. Munich
2013
How can industries create
affordable, maintainable, open
data stores which allow for the
“Merriman paradigm” in the
specific context of industrial data
mining requirements ?
39. Munich
2013
How we use MongoDB in our product
12 months ago, there were SQL parts
There was homegrown data serialization
Today, we only use MongoDB for any kind of
data storage
All network transports use inner BSON
chunks, extended for efficient real-time
object communication
42. Munich
2013
Remote
OPC UA Server
Endpoint
Remote
XML-DA Server
SPROX Protocol (Single Port TCP)
Secure Prioritized Realtime Object Xchange
Endpoint
Remote/Local
OPC DA Server
Endpoint
Remote/Local
OPC A&E Server
Endpoint
Remote /Local
OPC HDA Server
Endpoint
Connector Service
Core Service
43. Munich
2013
Remote
OPC UA Server
Endpoint
Remote
XML-DA Server
Schema Design:
• Multiple Databases
• Multiple Collections
Database Design:
• Replication (Redundancy)
• Port TCP)
SPROX Protocol (Single Sharding (Horizontal Scaling)
Secure Prioritized Realtime Object Xchange
Endpoint
Remote/Local
OPC DA Server
Endpoint
Connector Service
MongoDB
Remote/Local
OPC A&E Server
Different OPC Servers
Endpoint
Remote /Local
OPC HDA Server
Endpoint
Mongo BSON Object
Bulk Inserts
Core Service
44. Munich
2013
Third-Party Stack (API)
Command Application
•
•
•
•
•
•
Realtime Data Access
Component Registration
Historical Data Access
ComponentEvents
Alarms and Configuration
System Health Monitoring
Any MongoDB Driver
C++, C#, Java, …
Any MongoDB Driver
C++, C#, Java, …
Connector Service
Core Service
MongoDB
51. Munich
2013
Summary – MongoDB qualifies for
process data storage
It has the performance and the scalability options
required to store hi-freq data in huge amounts
Timestamp accuracy is sufficient
Schema (-less) flexibility fits the variant data structures,
originated in (OPC) source systems
Unbeatable value offer (both software and hardware
utilization)
It exposes ‘natural’ data structures which make any kind
of analysis fun
It satisfies IT people and engineers