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IBM Informix for
SQL & NoSQL
Keshav Murthy
rkeshav@us.ibm.com
Architect, IBM Informix
2
3

Applications must support mobile
− Interoperate with modern applications with agility
− Enterprise infrastructure

Ability to scale to big data
− Commodity hardware and software
− Use case are driving big data
− Data base layer meets web app requirements

Strategy: more interactions with customers
− Systems of engagement needed!
− 71% CIOs see move toward social/digital collaboration
− New class of applications are based on NoSQL
Global C-suite Study, http://www-935.ibm.com/services/us/en/c-suite/csuitestudy2013/
Explosion of mobile
devices
Business Trends Driving NoSQL
Adoption
4
SQL NoSQL
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
5
Martin Fowler says:
“aggregate-oriented”
What you're most likely to
access as a unit.
Key Value Store

Couchbase

Riak

Citrusleaf

Redis

BerkeleyDB

Membrain

...
Document

MongoDB

CouchDB

RavenDB

Couchbase

... Graph

OrientDB

DEX

Neo4j

GraphBase

...
Column

HBase

Hypertable

Cassandra

...
NoSQL Landscape
Informix
NoSQL Applications on
Informix

New Listener supports MongoDB drivers

Use the same driver for Informix & MongoDB
MongoDB
native Client
MongoDB
native Client
MongoDB
web
browser
MongoDB
web
browser
MobileMobile
Applications
MongoDB
Wire
Protocol
InformixMongoDB
driver
MongoDB
driver
6
Informix
Application Development
Tools
The MEAN Stack
Basic Translation
Terms/Concepts
8
Mongo/NoSQL Terms Traditional SQL Terms
Database Database
Collection Table
Document Row
Field Column
Index Index
{"name":"John","age":21, state:”CA”}
{"name":"Tim","age":28, Provence: “BC”}
{"name":"Scott","age":30, country: “UK”, status:1}
Name Age
John 21
Tim 28
Scott 30
Collection
Document
Key
Value
Table
Row
Informix JSON Store Benefits

Row locking on the individual JSON document

Large documents, up to 2GB maximum size

Ability to compress documents

Ability to intelligently cache commonly used documents

Use existing storage options and management tools.
9
•Supports B-Tree indexes on any key-value pairs.
•Typed indices could be on simple basic type (int, decimal,)
•Type-less indices could be created on BSON and use BSON
type comparison
•Translate ensureIndex() to CREATE INDEX
•Translate dropIndex() to DROP INDEX
Indexing
10
Mongo Operation SQL Operation
db.customers.ensureIndex(
{orderDate:1, zip:-1})
CREATE INDEX IF NOT EXISTS v_customer_2 ON
customer (bson_extract(data,‘orderDate')
ASC, bson_extract(data,‘zip') DESC) USING
BSON
db.customers.ensureIndex(
{orderDate:1},{unique:true})
CREATE UNIQUE INDEX IF NOT EXISTS
v_customer_3 ON customer
(bson_extract(data,'c1') ASC USING BSON
scale out (sharding) + High
Availability
App Server
Mongo Driver
Listener
JDBC
Enterprise repliation + Flexible Grid
App Server
Mongo Driver
Listener
JDBC
App Server
Mongo Driver
Listener
JDBC
App Server
Mongo Driver
Listener
JDBC
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
12
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
NoSQL + Relational
Internet of
Things
Hybrid Data Access:
relational tables & JSON
Collections
Relational Table JSON Collections
SQL API Standard ODBC, JDBC,
.NET, OData, etc.
Language SQL.
MongoDB
API (NoSQL)
Mongo APIs for Java,
Javascript, C++, C#, etc.
Direct SQL Access.
Dynamic Views
Row types
Mongo APIs for Java,
Javascript, C++, C#, etc.
Hybrid Data Access
14
SQL Tables
JSON Collections
TimeSeries
MQ Series
SQL APIs
JDBC, ODBC
SQL APIs
JDBC, ODBC
Informix
IWA – BLU Acceleration
GenBSON: SQL to BSON
Text search
Spatial
MongoDB
Drivers
MongoDB
Drivers
Timeseries(JSON)
Mongo Application
IBM Wire Listener
IDXs
Logs
Enterprise replication + Flexible Grid + Sharding
Distributed
Queries
Database
Tables
Tables
IDXs
Relational TablesRelational Tables
JSON CollectionsJSON Collections
SELECT bson_get(bson, ‘{}’) FROM customer
WHERE bson_value_lvarchar(bson,‘state’)=“MO”
SELECT bson_get(bson, ‘{}’) FROM customer
WHERE bson_value_lvarchar(bson,‘state’)=“MO”
db.customer.find({state:”MO”})db.customer.find({state:”MO”}) db.partners.find({state:”CA”})db.partners.find({state:”CA”})
SELECT * FROM partners WHERE state=“CA”SELECT * FROM partners WHERE state=“CA”
CustomerCustomer
partnerspartners
JSON JSON
Access RelationalAccess JSON
MongoAPI Accessing NoSQL & Relational
Data
Tables
JDBC connections
IDXs
Logs
Enterprise replication + Flexible Grid
Distributed
Queries
Database
Tables
Tables
IDXs
Relational TablesRelational Tables
JSON CollectionsJSON Collections
SELECT bson.customer::JSON,bson.state::lvarchar
FROM customer WHERE bson.state::lvarchar = “MO”
SELECT bson.customer::JSON,bson.state::lvarchar
FROM customer WHERE bson.state::lvarchar = “MO”
Select * from patners where state = “CA”;Select * from patners where state = “CA”;
CustomerCustomer
partnerspartners
Access RelationalAccess JSON
SQL Applications
SQL Accessing NoSQL & Relational Data
SQL TypesSQL Types
Informix for NoSQL and SQL
Access consistent data from its source
Avoid ETL, continuous data sync and conflicts.
Exploit the power of SQL, MongoAPI seamlessly
Exploit the power of RDBMS technologies in MongoAPI:
− Cost based Optimizer & power of SQL
− Spatial indices, Lucene text indices, and more.
Access all your data thru any interface: MongoAPI & SQL
Store data in one place and efficiently transform and use
them on demand.
Existing SQL based tools and APIs can access new data in
JSON

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Informix SQL & NoSQL -- for Chat with the labs on 4/22

  • 1. IBM Informix for SQL & NoSQL Keshav Murthy rkeshav@us.ibm.com Architect, IBM Informix
  • 2. 2
  • 3. 3  Applications must support mobile − Interoperate with modern applications with agility − Enterprise infrastructure  Ability to scale to big data − Commodity hardware and software − Use case are driving big data − Data base layer meets web app requirements  Strategy: more interactions with customers − Systems of engagement needed! − 71% CIOs see move toward social/digital collaboration − New class of applications are based on NoSQL Global C-suite Study, http://www-935.ibm.com/services/us/en/c-suite/csuitestudy2013/ Explosion of mobile devices Business Trends Driving NoSQL Adoption
  • 4. 4 SQL NoSQL 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
  • 5. 5 Martin Fowler says: “aggregate-oriented” What you're most likely to access as a unit. Key Value Store  Couchbase  Riak  Citrusleaf  Redis  BerkeleyDB  Membrain  ... Document  MongoDB  CouchDB  RavenDB  Couchbase  ... Graph  OrientDB  DEX  Neo4j  GraphBase  ... Column  HBase  Hypertable  Cassandra  ... NoSQL Landscape
  • 6. Informix NoSQL Applications on Informix  New Listener supports MongoDB drivers  Use the same driver for Informix & MongoDB MongoDB native Client MongoDB native Client MongoDB web browser MongoDB web browser MobileMobile Applications MongoDB Wire Protocol InformixMongoDB driver MongoDB driver 6 Informix
  • 8. Basic Translation Terms/Concepts 8 Mongo/NoSQL Terms Traditional SQL Terms Database Database Collection Table Document Row Field Column Index Index {"name":"John","age":21, state:”CA”} {"name":"Tim","age":28, Provence: “BC”} {"name":"Scott","age":30, country: “UK”, status:1} Name Age John 21 Tim 28 Scott 30 Collection Document Key Value Table Row
  • 9. Informix JSON Store Benefits  Row locking on the individual JSON document  Large documents, up to 2GB maximum size  Ability to compress documents  Ability to intelligently cache commonly used documents  Use existing storage options and management tools. 9
  • 10. •Supports B-Tree indexes on any key-value pairs. •Typed indices could be on simple basic type (int, decimal,) •Type-less indices could be created on BSON and use BSON type comparison •Translate ensureIndex() to CREATE INDEX •Translate dropIndex() to DROP INDEX Indexing 10 Mongo Operation SQL Operation db.customers.ensureIndex( {orderDate:1, zip:-1}) CREATE INDEX IF NOT EXISTS v_customer_2 ON customer (bson_extract(data,‘orderDate') ASC, bson_extract(data,‘zip') DESC) USING BSON db.customers.ensureIndex( {orderDate:1},{unique:true}) CREATE UNIQUE INDEX IF NOT EXISTS v_customer_3 ON customer (bson_extract(data,'c1') ASC USING BSON
  • 11. scale out (sharding) + High Availability App Server Mongo Driver Listener JDBC Enterprise repliation + Flexible Grid App Server Mongo Driver Listener JDBC App Server Mongo Driver Listener JDBC App Server Mongo Driver Listener JDBC 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
  • 12. 12 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 NoSQL + Relational Internet of Things
  • 13. Hybrid Data Access: relational tables & JSON Collections Relational Table JSON Collections SQL API Standard ODBC, JDBC, .NET, OData, etc. Language SQL. MongoDB API (NoSQL) Mongo APIs for Java, Javascript, C++, C#, etc. Direct SQL Access. Dynamic Views Row types Mongo APIs for Java, Javascript, C++, C#, etc.
  • 14. Hybrid Data Access 14 SQL Tables JSON Collections TimeSeries MQ Series SQL APIs JDBC, ODBC SQL APIs JDBC, ODBC Informix IWA – BLU Acceleration GenBSON: SQL to BSON Text search Spatial MongoDB Drivers MongoDB Drivers Timeseries(JSON)
  • 15. Mongo Application IBM Wire Listener IDXs Logs Enterprise replication + Flexible Grid + Sharding Distributed Queries Database Tables Tables IDXs Relational TablesRelational Tables JSON CollectionsJSON Collections SELECT bson_get(bson, ‘{}’) FROM customer WHERE bson_value_lvarchar(bson,‘state’)=“MO” SELECT bson_get(bson, ‘{}’) FROM customer WHERE bson_value_lvarchar(bson,‘state’)=“MO” db.customer.find({state:”MO”})db.customer.find({state:”MO”}) db.partners.find({state:”CA”})db.partners.find({state:”CA”}) SELECT * FROM partners WHERE state=“CA”SELECT * FROM partners WHERE state=“CA” CustomerCustomer partnerspartners JSON JSON Access RelationalAccess JSON MongoAPI Accessing NoSQL & Relational Data
  • 16. Tables JDBC connections IDXs Logs Enterprise replication + Flexible Grid Distributed Queries Database Tables Tables IDXs Relational TablesRelational Tables JSON CollectionsJSON Collections SELECT bson.customer::JSON,bson.state::lvarchar FROM customer WHERE bson.state::lvarchar = “MO” SELECT bson.customer::JSON,bson.state::lvarchar FROM customer WHERE bson.state::lvarchar = “MO” Select * from patners where state = “CA”;Select * from patners where state = “CA”; CustomerCustomer partnerspartners Access RelationalAccess JSON SQL Applications SQL Accessing NoSQL & Relational Data SQL TypesSQL Types
  • 17. Informix for NoSQL and SQL Access consistent data from its source Avoid ETL, continuous data sync and conflicts. Exploit the power of SQL, MongoAPI seamlessly Exploit the power of RDBMS technologies in MongoAPI: − Cost based Optimizer & power of SQL − Spatial indices, Lucene text indices, and more. Access all your data thru any interface: MongoAPI & SQL Store data in one place and efficiently transform and use them on demand. Existing SQL based tools and APIs can access new data in JSON