IBM Informix is a database management system that provides capabilities for handling different types of data including relational tables, JSON collections, and time series data. It uses a hybrid approach that allows seamless access to different data types using SQL and NoSQL APIs. The document discusses how Informix can be used to store and analyze IoT, mobile, and sensor data from devices and gateways in both on-premises and cloud environments. It also highlights the Informix Warehouse Accelerator for in-memory analytics and how Informix can be integrated with other IBM products and services like MongoDB, Bluemix, and Cognos.

1. IBM INFORMIX
putting it all together
John Miller,
Shawn Moe,
Keshav Murthy
IBM Informix Development

2. 2
Explosion of mobile
devices – gaming
and social apps
Advertising:
serving ads and
real-time
bidding
Social networking,
online
communities
E-commerce, social
commerce
Machine data and
real-time
operational
decisions
Smart
Devices
Internet of Things
Internet of
Things

3. 3
Explosion of mobile
devices – gaming
and social apps
Advertising:
serving ads and
real-time
bidding
Social networking,
online
communities
E-commerce, social
commerce
Machine data and
real-time
operational
decisions
Smart
Devices
Internet of Data, really
Internet of
Things
SQLSQL SQL, {JSON}, SpatialSQL, {JSON}, Spatial
{JSON},
TimeSeries
{JSON},
TimeSeries
SQL, {JSON}SQL, {JSON}
Simple,
{JSON},
Timeseries
Simple,
{JSON},
Timeseries
SQL, {JSON}SQL, {JSON}

4. 4
IoT Applications – IBM Reference Architecture
Gateway Operational Zone Warehouse/Mart Analytics Services and Contents
Shared Operational Information
Rule Engine
ETL
Real-Time
Data Store
Hadoop
Video
Analytics
Big Data
Explorer
Analytic
Tools
Connected Device
Analyzed Data
MapReduce
HDFS/GPFS
Device
Management
:
Predictive
Maintenance
Traffic
Optimization
Driving
Behavior
Incident
Analysis
Infotainment
Service
Raw Data
Summarized
Data
Notification
Analytic
Report
B2C/B2B
Portal
Admin
Console
Operator
Console
LocalIntelligence
NetworkSupport
Stream
Processing
ETL
RDB
DataMart
SOE Data
Video
Management
Asset Data
Management
Master Data
Management
Reference
Data Hub
Video Data
..
Environment
Data, etc.
Other
Data
Local
Database

5. © 2014 IBM Corporation5
IBM Cloud: Think it. Build it. Tap into it.
IoT Solutions, an architecture.
Collection of data for all
sensors
Data from
other kinds of
sensors
Consumer / Business
Sensors in the
home
Informix TimeSeries Service
NoSQL, Relational,
Timeseries & Spatial
storage & analytics
Informix Warehouse
Accelerator
SPSS/Cognos
MessageSight /
MQTT
SoftLayer /
BlueMix
BigInsights
Gateways for data
consolidation
Infosphere Streams
(no gateway)
= IBM products = IBM Informix Relational Database
In-memory analytics
Predictive analytics
and dashboard
Cloud infrastructure
Hadoop
Publish /
Subscribe
Real-time
analytics

6. • Individual Car Recognition in the parking zone
•Composite sensors to transmit license image
•Cloud service to recognize the car plate number
•Location tracking
• Individual Car Recognition in the parking zone
•Composite sensors to transmit license image
•Cloud service to recognize the car plate number
•Location tracking

7. IBM Informix developer edition. Download Now:
http://www-03.ibm.com/software/products/en/infodeveedit
IBM Informix developer edition. Download Now:
http://www-03.ibm.com/software/products/en/infodeveedit

8. Handling Big Data

9. IBM Bluemix

10. 10
SQL {NoSQL:JSON}
Define Schema first Write the program first
Relational Key-value, Document, column
family, graph and text
Changing schema is hard Assumes dynamic schema
Scale-up Scale-out
ACID consistency BASE consistency
Transactions No Transactions
SQL Proprietary API; Sometimes has
the “spirit” of SQL

11. 11
SQL Timeseries
Define Schema first Create Timeseries Row Type
Relational Timeseries Optimized with
projection to relational
Changing schema is hard Changing schema is hard;
Change is easy with
Timeseries({JSON})
Scale-up Scale-up & Scale-out
ACID consistency ACID consistency
SQL SQL extensions.

12. Data Management: devices to Cloud
Enterprise replication + Flexible Grid
App Server
JDBC
App Server
Mongo Driver
Listener
Informix/1
Primary
Informix/1
SDS/HDR
Informix/1
RSS
Informix/2
Primary
Informix/2
SDS/HDR
Informix/2
RSS
Informix/3
Primary
Informix/3
SDS/HDR
Informix/3
RSS
Informix/4
Primary
Informix/4
SDS/HDR
Informix/4
RSS
Informix/5
Primary
Informix/5
SDS/HDR
Informix/5
RSS
Informix/6
Primary
Informix/6
SDS/HDR
Informix/6
RSS
Mongo APIMongo API
Node.JS
Express.JSExpress.JS
AngularJSAngularJS
REST APIsREST APIs
NoSQL SQL
Devices
Devices
Gateway
Gateway
CloudCloud
Informix warehouse Accelerator

13. Informix: All Together Now!
13
SQL Tables
JSON Collections
TimeSeries
MQ Series
SQL APIs
JDBC, ODBC
SQL APIs
JDBC, ODBC
Informix
IWA – BLU ACCELERATION
GENBSON: SQL to {BSON}
MongoDB
Drivers
MongoDB
Drivers
TEXT SEARCH
SPATIAL
TIME SERIES {BSON}

14. Data Model
Should NOT
restrict Data
Access

15. Universal
Schema
Seamless
Access

16. SQL APISQL API
MongoDB API
(NoSQL)
MongoDB API
(NoSQL)
Relational TableRelational Table JSON CollectionsJSON Collections
Standard ODBC, JDBC,
.NET, OData, etc.
Language SQL.
Standard ODBC, JDBC,
.NET, OData, etc.
Language SQL.
Mongo APIs for Java,
Javascript, C++, C#,...
Mongo APIs for Java,
Javascript, C++, C#,...
Direct SQL Access.
Dynamic Views
Row types
Mongo APIs for Java,
Javascript, C++, C#,...
Mongo APIs for Java,
Javascript, C++, C#,...
Hybrid Access: SQL &
JSON

17. SQL APISQL API
MongoDB API
(NoSQL)
MongoDB API
(NoSQL)
Relational TableRelational Table JSON CollectionsJSON Collections
Standard ODBC, JDBC,
.NET, OData, etc.
Language SQL.
Standard ODBC, JDBC,
.NET, OData, etc.
Language SQL.
Mongo APIs for Java,
Javascript, C++, C#,...
Mongo APIs for Java,
Javascript, C++, C#,...
Direct SQL Access.
Dynamic Views
Row types
Direct SQL Access.
Dynamic Views
Row types
Mongo APIs for Java,
Javascript, C++, C#,...
Mongo APIs for Java,
Javascript, C++, C#,...
JSON CollectionsJSON CollectionsJSON CollectionsJSON Collections
Standard SQL/ext
JDBC/ODBC
JSON Support
Standard SQL/ext
JDBC/ODBC
JSON Support
Virtual Table
JSON support
Virtual Table
JSON support
TimeseriesTimeseriesJSON CollectionsJSON Collections TimeseriesTimeseriesRelational TableRelational Table JSON CollectionsJSON Collections TimeseriesTimeseries
Hybrid Access:
SQL, JSON & Timeseries
Standard SQL/ext
JDBC/ODBC
JSON Support
Standard SQL/ext
JDBC/ODBC
JSON Support
TimeseriesTimeseries
Standard SQL/ext
JDBC/ODBC
JSON Support
Standard SQL/ext
JDBC/ODBC
JSON Support
TimeseriesTimeseries
Virtual Table
JSON support
Virtual Table
JSON support
Standard SQL/ext
JDBC/ODBC
JSON Support
Standard SQL/ext
JDBC/ODBC
JSON Support
Virtual Table
JSON support
Virtual Table
JSON support
TimeseriesTimeseries
Standard SQL/ext
JDBC/ODBC
JSON Support
Standard SQL/ext
JDBC/ODBC
JSON Support
Virtual Table
JSON support
Virtual Table
JSON support
TimeseriesTimeseries
Standard SQL/ext
JDBC/ODBC
JSON Support
Standard SQL/ext
JDBC/ODBC
JSON Support
Virtual Table
JSON support
Virtual Table
JSON support
TimeseriesTimeseries
Standard SQL/ext
JDBC/ODBC
JSON Support
Virtual Table
JSON support
Virtual Table
JSON support

18. SQL APISQL API
Mongo API
(NoSQL)
Mongo API
(NoSQL)
Relational TableRelational Table JSON CollectionsJSON Collections
Standard ODBC, JDBC,
.NET, OData, etc.
Language SQL.
Standard ODBC, JDBC,
.NET, OData, etc.
Language SQL.
Mongo APIs for Java,
Javascript, C++, C#,...
Mongo APIs for Java,
Javascript, C++, C#,...
Direct SQL Access.
Dynamic Views
Row types
Direct SQL Access.
Dynamic Views
Row types
Mongo APIs for Java,
Javascript, C++, C#,...
Mongo APIs for Java,
Javascript, C++, C#,...
JSON CollectionsJSON CollectionsJSON CollectionsJSON Collections
Standard SQL/ext
JDBC/ODBC
JSON Support
Standard SQL/ext
JDBC/ODBC
JSON Support
Virtual Table
JSON support
Virtual Table
JSON support
TimeseriesTimeseriesJSON CollectionsJSON Collections TimeseriesTimeseriesRelational TableRelational Table JSONJSON TimeseriesTimeseries
Spatial
Text
Spatial
Text
Standard SQL
JDBC/ODBC
JSON Support
JSON SupportJSON Support
Hybrid Access:
SQL, JSON, Timeseries &
Spatial

19. Mapping A JSON To A SQL Table
CREATE TABLE photos(data BSON);
SELECT data.GPSLatitude::lvarchar as GPSLatitude,
data.GPSLongitude::lvarchar as GPSLongitude,
data.Make::varchar(64) as Make,
data.oateTimeoriginal::datetime year to day as dt,
data.exposuretime::int
data.pixelxdimension::float,
data.pixelydimension::float
FROM photos;

20. 20
Timeseries on JSON
CREATE ROW TYPE info( stime datetime year to fraction(5),
jdata bson);
CREATE TABLE iotdata(id int primary key, tsdata timeseries(info) );
INSERT INTO iotdata VALUES(472,'origin(2014-04-23 00:00:00.00000), …,
regular,[({“temp":78, “wind":7.2, “loc":“Miami-1 "})]');
INSERT INTO iotdata values(384,'origin(2014-04-21 00:00:00.00000), …,
regular,[({“sleep": 380, “steps":7423, “name":"Joe "})]');
SELECT GetFirstElem(tsdata,0)::row(timestamp datetime year to
fraction(5), jdata json) FRONM tj;
(expression) ROW('2014-04-21
00:00:00.00000','{“sleep":380,“steps":7423,“name":"Joe "}')
…

21. 21
Timeseries on JSON
CREATE TABLE iotvti(id INT PRIMARY KEY,
stime DATETIME YEAR TO FRACTION(5)),
jdata BSON);
SELECT id,
jdata.temp::int,
jdata.loc::varchar(32)
FROM iotvti WHERE jdata.temp > 75;
db.iotvti.find({“jdata.temp”:{$gt:75},
{jdata:1}, {jdata:1});
{“temp":75, “wind":7.2, “loc":“Miami-1 "}

22. 22
Informix REST API
REpresentational State Transfer
http://<hostname>[:<port#>]/<db>/<collection>
Integrated into Informix
GET /demo/people?sort={age:-1}&fields={_id:0,lastName:0}
RESPONSE: [{"firstName":"Anakin","age":49},
{"firstName":"Padme","age":47},
{"firstName":"Luke","age":31},
{"firstName":"Leia","age":31}]
GET /stores_demo/ts_data_v?query={loc_esi_id:"4727354321046021"}

23. 23
A v a ila b le M e th o d s
M e th o d P a th D e s c r ip tio n
P O S T / C r e a te a n e w d a ta b a s e
P O S T /d b C r e a te a n e w c o lle c tio n
P O S T /d b /c o lle c tio n C r e a te s a n e w d o c u m e n t
G E T / D a ta b a s e lis tin g
G E T /d b C o lle c tio n lis tin g
G E T /d b /c o lle c tio n Q u e r y th e c o lle c tio n
D E L E T E / D r o p a ll d a ta b a s e s
D E L E T E /d b D r o p a d a ta b a s e
D E L E T E /d b /c o lle c tio n D r o p a c o lle c tio n
D E L E T E /d b /c o lle c tio n ? q u e r y = { ...} D e le te d o c u m e n ts th a t s a tis fy th e
q u e r y fr o m a c o lle c tio n
P U T /d b /c o lle c tio n U p d a te a d o c u m e n t
INFORMIX REST API

24. ODBC, JDBC connections
Informix Dynamic Server
Tables
Tables
Relational Tables
and views
Relational Tables
and views
JSON CollectionsJSON Collections
{Customer}{Customer}
partnerspartners
SQL & BI Applications
{Orders}{Orders}
CRMCRM
InventoryInventory
Tables
Timeseries TablesTimeseries Tables
{mobile/devices}{mobile/devices}
Analytics

25. Informix Warehouse
Accelerator
Informix
Database Server
Informix warehouse
Accelerator
BI Applications
Data mart Tools
Ready
IBM Smart
Analytics Studio

26. Informix Dynamic Server
Tables
Tables
Relational Tables
and views
Relational Tables
and views
JSON CollectionsJSON Collections
{Customer}{Customer}
partnerspartners
SQL & BI Applications
{Orders}{Orders}
CRMCRM
InventoryInventory
Tables
Timeseries TablesTimeseries Tables
{Orders}{Orders}
Text index (BTS)
spatial indices
Text index (BTS)
spatial indices
Informix Warehouse Accelerator – In-Memory Query Engine
ODBC, JDBC connections
SQL Apps/Tools
MongoDB Drivers
NoSQL Apps/Tools
Mongo clientMongo client
Node.JS
Express.JSExpress.JS
AngularJSAngularJS

27. IWA: Complex Data Analysis
Informix Database Server
Informix Warehouse Accelerator
BI Applications
Informix Database Server
Factdim1
Dim4 - View
dim3
dim2
dim2
Informix
IoT ApplicationsLoB Apps
IoT Applications
BI Applications
Mobile Apps
Informix

28. IWA: Complex Data Analysis
Informix Database Server
Informix Warehouse Accelerator
Informix Database Server
SQL Table
SQL View
{JSON}
SQL Table
SQL Table
Informix
LoB Apps
IoT
Applications
BI Applications
Mobile Apps
Informix
Timeseries
{JSON}
{JSON}
Cognos
SQL Table

29. ODBC, JDBC connections
Informix Dynamic Server
Tables
Tables
Relational Tables
and views
Relational Tables
and views
JSON CollectionsJSON Collections
{Customer}{Customer}
partnerspartners
SQL & BI Applications
{Orders}{Orders}
CRMCRM
InventoryInventory
Tables
Timeseries TablesTimeseries Tables
{mobile/devices}{mobile/devices}
Analytics
Informix warehouse Accelerator

30. Hybrid Power for IoT Apps
Right type for right data – SQL, JSON, Timeseris,
Spatial, Text
Variety of APIs: REST, JDBC, ODBC
Platform & device options
Right size for the right problem – Customize
What’s good for embed is good good for the cloud
Continuous availability
Accelerate with Informix Warehouse Accelerator
Mix it in with Bluemix
Scale-up, Scale-out

31. IBM Informix developer edition.
http://www-03.ibm.com/software/products/en/infodeveedit
IBM Informix developer edition.
http://www-03.ibm.com/software/products/en/infodeveedit
Download Now!
Download Now!

32. Thank you