This document summarizes a presentation on using NoSQL databases as message stores with messaging architectures. The presentation introduces common messaging patterns like message store, claim check, and aggregator. It then discusses using Redis, Oracle NoSQL, and MongoDB as message stores and shows examples implementing messaging patterns with Spring Integration using these NoSQL databases. The document includes an architecture diagram and screenshots from demos of a sample application.

1. MESSAGING ARCHITECTURES WITH NOSQL
DATABASES AS MESSAGE STORES
JavaOne 2012 Conference (#JavaOne)
Srini Penchikala (@srinip)
10.4.12

2. GOALS OF THIS PRESENTATION
 NoSQL databases to store messages with focus on EIP
Patterns
 Target Audience: Integration Architects and Developers
 Redis, Oracle NoSQL, and MongoDB databases
 Demos (Java application)
 Not a NoSQL or Messaging intro presentation
 Format:
 50 min presentation & demos
 10 min for Q&A 2

3. WHO AM I
 Software Architect
 Co-author of Spring Roo in Action book
 Editor at InfoQ.com
 Background:
 Financial services industry
 Regulatory compliance (PCI & FISMA)
 J2EE architecture model
 Scrum for software development
 Agile (v./and) Architecture
3

4. QUICK POLL
 Who is using EIP Patterns?
 Spring Integration?
 NoSQL?
 Spring Data?
4

5. TODAY’S DISCUSSION
 Enterprise Integration Patterns
 NoSQL databases
 NoSQL as message stores
 MongoDB / Redis / Oracle NoSQL Database
 Spring Data
 Spring Integration framework
 Sample Java application
 Best Practices
 Conclusions
5

6. MESSAGING
 Advantages
 Limitations
 Message Loss
 Performance
 Security
 Availability
 Design Considerations*
6
*Main focus of this presentation

7. MESSAGING PATTERNS
 Message Store
 Claim Check
 Queue Channel
 Aggregator
 Resequencer
 Control Bus*
 Wire Tap*
7
URL: http://www.eaipatterns.com
*System monitoring and management

8. MESSAGE STORE
 Store Messages in a persistent
store (e.g. Database)
 Why Message Store?
 Performance
 Availability
8
http://www.eaipatterns.com/MessageStore.html

9. MESSAGE STORE USE CASES
 Message buffering
 Aggregator
 Resequencer
 Queue Channel
 Message loss prevention
 Claim Check
9

10. CLAIM CHECK
 Store message data in a
persistent store and pass a
Claim Check to subsequent
components.
 These components can use
Claim Check to retrieve the
stored information.
10
http://www.eaipatterns.com/StoreInLibrary.html

11. PERSISTENCE
 Key Value Data Store
 Redis
 Oracle NoSQL
 Document Database
 MongoDB
 GemFire
 JDBC
 In-Memory
11

12. NOSQL DATABASES
 Redis
 Redis-based MessageStore
 Publish-Subscribe Messaging adapters
 Oracle NoSQL Database
 Distributed key-value database
 ACID transactions
 Administration via Web console or CLI
 Use Cases: Online Display Advertising & Mobile Social Gaming
 MongoDB
 Document database
12
http://www.redis.io, http://www.mongodb.org
http://www.oracle.com/technetwork/products/nosqldb/overview/index.html

13. SPRING INTEGRATION
 Extension of the Spring framework
 Implements Enterprise Integration Patterns (EIP)
 Lightweight messaging
 Integration with external systems via declarative adapters
 Separation of concerns
13
*http://www.springsource.org/spring-integration

14. SPRING DATA
 Spring applications that use new data access technologies
 Non-relational databases
 Map-reduce frameworks
 Current Implementations:
 Big Data (Apache Hadoop)
 Data-Grid (GemFire)
 Key Value Stores (Redis)
 Document Stores (MongoDB)
 Graph Databases (Neo4j)
 Column Stores (Hbase) 14
*http://www.springsource.org/spring-data

15. SPRING ROO
 Rapid Java application development
 Nice integration for Spring Integration and Spring Data
frameworks
15
*http://www.springsource.org/spring-data

16. MESSAGE STORE “STRATEGY”
 Based on Strategy design pattern
 MessageStore strategy
 Used by QueueChannel and ClaimCheck patterns
 MessageGroupStore strategy
 Used by Aggregator and Resequencer patterns
 Implementations
 SimpleMessageStore (In-memory, Map-based)
 JdbcMessageStore (uses a relational database via JDBC)
 NoSQL Data Store
16

17. MESSAGE STORES
17
Message Store
Simple (In-Memory)* NoSQLJDBC
Redis* MongoDB* Oracle NoSQL* GemFire
*Covered in the sample application demos

18. SAMPLE APPLICATION
 Oracle NoSQL Database
 Redis
 Spring Integration
 Spring Data
 JUnit
18
*Code will be posted on Github

19. DEMO APPLICATION - USE CASE 1 (CLAIM CHECK)
19
Message
Header
Enricher
Message
Store
(In-Memory)
Claim
Check (In)
Queue
Channel
Transformer
Claim
Check (Out)
Message
Store
(MongoDB)

20. MESSAGE STORE DEMO 1
 In Memory Message Store
 MongoDB
20

21. DEMO APPLICATION - USE CASE 2 (AGGREGATOR)
21
Message Aggregator
Message
Store
(Redis)
Queue
Channel
Transformer
Message
Store (Oracle
NoSQL)

22. ARCHITECTURE DIAGRAM
22
Source:
http://static.springsource.org/spring-integration/docs/latest-ga/reference/html/samples.html

23. MESSAGE STORE DEMO 2
 Redis Demo
23

24. CUSTOM MESSAGE STORE IMPLEMENTATION
 MessageStore interface
 CustomOracleNoSqlMessageStore class
24

25. MESSAGE STORE DEMO 3
 Oracle NoSQL Message Store
25

26. MESSAGE STORE LIMITATIONS
 When using JdbcMessageStore, only Serializable data is
persisted by default
 Different instance of some Spring Bean is returned upon
deserialization for headers that represent certain types of
data
 Temporary Reply Channel issue
26

27. CONCLUSIONS
 Message Persistence
 Message Store pattern
 Claim Check
 NoSQL and Messaging
 “One Size Fits All” fits nothing
27

28. RESOURCES - BOOKS
28
Enterprise Integration Patterns
(http://eaipatterns.com)
Spring Integration in Action
(http://www.manning.com/fisher)
Spring Roo in Action
(http://www.manning.com/rimple)

29. RESOURCES
 Enterprise Integration Patterns (http://www.eaipatterns.com)
 Spring Integration (http://static.springsource.org/spring-
integration/reference/html)
 Spring Integration Support for Redis (http://static.springsource.org/spring-
integration/reference/html/redis.html)
 Oracle NoSQL Database
(http://www.oracle.com/technetwork/products/nosqldb/overview/index.html)
 http://blog.codecentric.de/en/2012/04/spring-data-redis/
 Message Store (http://www.eaipatterns.com/MessageStore.html)
 Redis (http://redis.io/topics/pubsub)
 MongoDB
 Spring Data
 Spring Data Redis
 Sample Application on Github
29

30. THANK YOU
 Contact Information
 http://www.infoq.com/author/Srini-Penchikala
 srinipenchikala@gmail.com
 @srinip
 http://srinip2007.blogspot.com
 Spring Roo in Action Book
 Questions?
30

31. BONUS SLIDES
 Bonus Slides
31

32. MESSAGING GATEWAYS
 JMS
 AMQP
 File
 FTP/SFTP
 HTTP (REST)
 WS (SOAP/POX)
 JDBC
 Twitter
 MongoDB
 Redis 32

33. CONTROL BUS
 Administer a messaging
system distributed across
multiple platforms
 Uses same messaging
mechanism used by
application data, but uses
separate channels to
transmit data for the
management of message
flow components 33
http://www.eaipatterns.com/StoreInLibrary.html

34. WIRE TAP
 Inspects messages that
travel on a point-to-point
channel
 Recipient List into the
channel that publishes
each incoming message to
the main channel and a
secondary channel
34
http://www.eaipatterns.com/WireTap.html

35. XML CONFIGURATION OF MESSAGE STORE
<bean id="redisMessageStore"
class="org.springframework.integration.redis.store.RedisMess
ageStore">
<constructor-arg ref="redisConnectionFactory"/>
</bean>
<int:channel id="somePersistentQueueChannel">
<int:queue message-store="redisMessageStore"/> <int:channel>
<int:aggregator input-channel="inputChannel" output-
channel="outputChannel" message-store="redisMessageStore"/>
35

36. MONITORING
 Control Bus
 JMX
36

37. MONITORING SCREENSHOT
 Screenshot
37

38. MONITORING (DEMO 4)
 DEMO
38