The company presentation of sones

1. Create and Uncover Relationships.

2. About sones
sones GraphDB
is the first database for
cloud computing that
makes associations
between complex data just
like the human brain.
(*)e.g.:
Seman-c
Web
data,
workflows,
pictures,
personal
documents,
loca-on,
sensor
data,
eCommerce
items,
Facebook,
TwiAer,
blogs,
mobile
apps,
configura-on
data,
your
email
inbox,
CRM
data

3. Company history
Series A financing
GraphDB as an round with TGFS
GraphDB 1.0 open source
version Talend data
T-Venture Initial proof of à OSE 1.1 – integration
sones GmbH
founded invests concept 5,000 downloads
Customer saves during the first Enterprise Edition
First on 100 servers month license for telcos,
The basic
concept of the customer: T- with version 1.0 web, data analysis
DB structure is Online GraphDB Cloud
developed (prototypes) Start of OEM and Edition on Azure New CEO and
partner sales expanded
strategy management
Financing with
seed capital
3 employees

4. Information - the capital of today and tomorrow
§ How people access information today:
• using the Web (no boundaries, unstructured) or
• using databases (structured, boundaries)
§ How people will access information in the
future:
Sones GraphDB
• using the Semantic Web, ontologies
(no boundaries, structured, automated)

5. The current market
90% of data traffic
today is
unstructured
(worldwide)
In 2011, this digital
universe will be 10
Videos, photos, times bigger than it
articles, user profiles, was in 2006 (IDC
news, groups, prediction)
events...
§ Cloud
compu-ng
data
management’s
unsolved
issues
(Cloud
Compu-ng,
Hype
Cycle,
Gartner):
§ Data
security,
data
portability,
user
controls,
reliability,
concurrency
and
dynamic
connec4ons
between
data
records
(#)
(data
has
to
be
shi:ed
from
one
data
center
to
another
to
process
the
informa4on)

6. Database Evolution
Graph-based concepts - latest innovation
Olap - and other
concepts for
real time analytics
Graph based
Content /
Application /
Analytics / Search
Object. Joe
Person Lives in Palo Alto IBM
IBM.com
Web Site
City Company
Relational Database
Database
Publisher of
Subscriber to Fan of Lives in
Employee of Sue
Niche-products,
Jane Person
Dave.com
ERP, CRM, …
RSS Feed Coldplay
Band
Fan of
Design
Person
Friend of
Dominating the Developers
Source of
Dave.com
Team
Group Member
of
Married to
Bob
Depiction of
123.JPG
Photo
Weblog Person
market Author of
Dave
Member of
Person
Stanford
AlumnaeMember of
Depiction of
Group
Member of
Hierarch. Database
Nearly “died out”
Key value based
concepts for
search and Web
60s 70s 80s 90s Since 2000 Today
Search, Cloud Computing

7. The database world
The innovation:
IBM.com
Joe Website
Person Lives in Palo Alto IBM
City Company
Publisher of
Fan of
Subscriber to Lives in
Employee of
Sue
Jane Person
Dave.com Fan of
Coldplay Person
RSS feed Friend of
Band Member
of
Design Depiction of
Married to
Source of Team
Member
Group 123.JPG
of
Dave.com Bob Photo
Web log Person
Depiction of
Member of
Stanford Member of
Dave
Author of Alumnae
Person
Group
Member of

8. What is sones GraphDB?
sones GraphDB:
§ A new type of object-oriented, graph-based database management
system
§ Enables efficient storage, management and evaluation of complex,
highly connected data records
§ Combines the advantages of file storage with the possibilities of a
database management system
§ Unstructured data and information (e.g., video files), semi-structured
data (metadata, e.g., log files) and structured data (similar to SQL) can
be linked to each other, which makes it possible for users to manage
this data themselves and evaluate when necessary

9. What makes us different?
Persistence: Flexible data
Storage on a modeling
non-volatile while the
storage system is
medium running

10. We do it differently
§ Information and data are saved in object networks instead of
tables.
§ The original data structure is maintained.
§ New paradigm:
§ Linking logic and data. Improved efficiency-real-time.
§ New functions for large numbers of queries on highly complex,
distributed, dynamic data.
•Fewer processing steps required.
•Cost advantages, competitive advantages

11. Universal data access
Personalized recommendations Social CRM
New database applications
Scaling at the push of a button Targeting
GraphDB SOAP
Web Universal data access REST
DAV
Automatically generates metadata from Consolidation and links to other Links to your
images, videos, music and documents information corporate data
Metadata Image data Public profile data
… Type Compression Can be linked with
Dimensions Camera corporate data on
Width Photographer Facebook
Relational Height Price Increased
data silos Resolution
Bit depth
… information density
Universal access Your data remains Develop your own
no matter where your data consistent even when solutions using a
is stored modeled while the flexible
system running data structure

12. Easy to manage
Easy-to-learn GQL query
language
MySQL query
SELECT w.word AS wort, k.sig AS sig FROM co_s k,
words w WHERE k.w1_id=(SELECT w_id
FROM words w WHERE word = “Laptop”) AND
k.w2_id=w.w_id ORDER BY k.sig DESC LIMIT
10;
Index-based storage, simplifies GQL query
storage and search processes
FROM Word SELECT Cooccurrences.TOP(10)
WHERE Content = ‘Laptop’;
Index
Can be scaled as
No. Subject you like – our
… … BeAer
solution easily grows
… …
… …
Performance
with your demands
… … =
… … Cost
savings
Rela-onal
Database
SEARCH Increasing
amount
of
connected
data

13. Real-time analytics
Recognizing and evaluating
multidimensional relationships
Universal analytics
Analysis and
prioritization
Relevant
information

14. Low TCO
Highly scalable
Complex queries as in-depth as
desired on the GraphDB call for less
processing power due to their graph
structure
Optimized processing power, up to
No double data
300% greater performance when
storage for data
handling
processing and
semi-structured data
evaluation
JPEG …
$ €

15. Solution approaches
Cross-system
duplicate recognition
Point of sale
Real-time recommendations
Analyses of customer
behavior
e.g.: churn detection
15

16. Locations
sones GmbH sones GmbH
Headquarters RD Lab
Schillerstraße 5 Eugen-Richter-Straße 44
04109 Leipzig 99085 Erfurt
Germany Germany
Mail: info@sones.de Mail: info@sones.de
Tel.: +49 (0) 341/ 3929 680 Tel.: +49 (0)361/ 3026 250
Fax: +49 (0) 361/ 2445 008 Fax: +49 (0)361/ 2445 008

17. Appendix
Application examples
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18. Web
§ Image portal - Increases sales of images since the
right image can be found much more quickly or is
automatically recommended
§ AB testing - Fast and easy evaluation of marketing
campaigns Real-time analysis also possible during
implementation
§ Click-path analysis - e.g., via which paths do
customers access the portal
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19. Web / content
§ Link building – Automatically links relevant pages/
content, checks completeness of references, makes
automatic recommendations of links to appropriate
pages (according to topic or other criteria).
§ SEO – Optimized search results (e.g., with Google).
The system does not directly link pages but generates
“link chains” that provide the desired depth (e.g., 4
plus x).
§ Content management - Providing the right content to
the right user in the right context at the right time
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20. Universal data access
§ Enterprise Search/Enterprise Storage - Access to all
data present internally regardless of their data silo.
With the option of saving changes in that same
location. Supplements internal data with external
information from the Web (e.g. blogs/web portals/
social networks).
§ Central metadata repository - Universal data
access layer, centrally manage corporate data. Link
data from diverse editorial sources (images, articles,
etc.)
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21. Social graph
§ Analysis of user behavior - How do visitors/customers
behave on the corporate website?
§ Customer/user group evaluation
§ SRM (social CRM) – Supplementing existing customer
data with customer data from sources such as social
networks, e.g., Facebook. Intention: to develop a
holistic picture of the customer. When customer X
calls, sales agents/customer agents can access both
the internal customer status as well as information on
the customer that they have posted on blogs, social
networks, etc.
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22. Social net
§ Campaign management - Addressing campaigns to
the right customers at the right time.
§ Automatic categorization (e.g., job profiles for job
portals) - Semantic categorization in order to increase
the quality of job ads, etc., on the portal.
§ Social networks - Real-time friend-of-a-friend
calculation. Who do I know through WHOM?
Customizable path query with desired depth possible
ad-hoc.
22

23. eCommerce
§ eCommerce - Recommendations regarding the
right products made to the right customers at the
right time (customer-specific advertising), regional
targeting. Goal: To increase the number of items
sold.
§ eCommerce - Optimizing costs by reducing the
number of items returned – Automatic recognition
of “safe” returns, conducting pre-defined
processes, e.g., recommending suitable products,
increasing costs for shipping, etc.
23

24. Social commerce
§ Adding social commerce, i.e., recommendations
from/to friends in the friendship graph (i.e., also multi-
hop!) or
§ product graphs (shared shopping possible)
§ for members of a group or similar shopping behaviors
§ e.g., same brand regarding individual products
§ e.g., same interests/groups/rated products
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25. Visualization
§ Affiliation management – Who is affiliated with which
companies? Direct storage of related information such
as minutes of meetings, company agreements, etc.
§ Visualization – Simple, interactive depiction of
relationship networks/connections/relationships.
Intuitive use (e.g.,. via Silverlight)
§ Geomapping - Linking the data mentioned above with
geoinformation Where are customers/subscribers
located? (and why?)
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26. Miscellaneous
§ Recalls, e.g., for cars: Ad-hoc report of all the people
who purchased a car in which the defective part is
installed.
§ Parts tracking – Who installed which part when?
Which supplier can deliver a specific product at a
certain time for the lowest price?
§ Semantic Web – social tagging, processing user
generated content, crowd sourcing, social media
monitoring
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27. CMDB
§ Configuration management database
• Definition according to Wikipedia In the IT Infrastructure Library (ITIL)
context, a CMDB is a database that is used to access and manage
configuration items. All IT resources are classified as configuration items
(CI) in the context of IT management. […] In this context, this refers to the
existing pool and the interdependencies of the objects being managed.
• Specification: federation (metadata management) / reconciliation (target/
current state comparisons) / mapping visualization / synchronization
sones graphDB can be described as the only real
CMDB
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28. Disclaimer
General Disclaimer
This document is not to be construed as a promise by any participating company to develop, deliver,
or market a product. It is not a commitment to deliver any material, code, or functionality, and should
not be relied upon in making purchasing decisions. sones GmbH makes no representations or
warranties with respect to the contents of this document, and specifically disclaims any express or
implied warranties of merchantability or fitness for any particular purpose. The development, release,
and timing of features or functionality described for sones products remains at the sole discretion of
sones. Further, sones GmbH reserves the right to revise this document and to make changes to its
content, at any time, without obligation to notify any person or entity of such revisions or changes. All
sones marks referenced in this presentation are trademarks or registered trademarks of sones GmbH
and other countries. All third-party trademarks are the property of their respective owners.
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