The document discusses the benefits of using multiple programming languages and data stores, or a "polyglot" approach, for modern applications. A polyglot approach allows using the right tool for each task, rather than trying to force a single technology to fit all needs. This improves performance, scalability, and the ability to adapt applications to changing requirements compared to traditional monolithic architectures. The document provides examples of when to use different languages and data stores and concludes that a polyglot approach makes applications easier to maintain over time.

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Proud to be Polyglot!
Tugdual Grall
@tgrall
June 11, 2015

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Modern Applications
• Modern Applications Must
• Manage any type of data
• Scale
• Be fault tolerant
• Adapt to change

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Current Architecture
• Mono-Technology
• Single “language/architecture”
• Single Database : RDBMS
• One size fits all approach
JSP/JSF
Services
Messaging
JTA
DAO/JPA

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Is it good for me?
• Many Files
• XML, Sources, Configuration, …
• Does Hibernate/JPA is good for all?
• Impedance mismatch
• Need to scale
• From 0 to 50 millions users in 6 weeks
• 1Tb of data each day
• How easy is to add new features?
• Changing code, updating data structure, …
• And all this for yesterday !

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One size does NOT fit all!

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Let’s look at our data…
6

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Big Data

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Big Users
http://www.theconnectivist.com/ & Cisco

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. . .
App Server
RDBMS
Application
Scale out
Add more “Web” servers
RDBMS
Scale Up
Get bigger server
Stay up!…. and Scale

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Scaling out RDBMS
• Run many RDBMS Servers
• Data could be partitioned
• Done by the application code
• Caching Layer
. . .
App Server
. . .
Memcached
. . .
MySQL

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NoSQL to Scale Out!
. . .
NoSQL
App Server
. . .
Application
Scale out
Add more “Web” servers
NoSQL
Scale Out
Add more servers

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Operational vs Analytics Databases
Warehouse,AnalyticsApplications, Interactions

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Polyglot Persistence
Big Data/Analysis NoSQL RDBMS
• Log Capture
• Recommendations
• Predictions
• Ad Campaign
• Products
• User Profiles
• Game Actions
• Sessions
• Shopping Cart
• Financial Data
• Reporting

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Data Service Layer
• Wrap data call in Services
– loosely coupled
. . .
App Server

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Use Case : Personalization
WebSite / Application
Personalization Database
Data Processing
Logs
Application
Data

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Use Case : Mobile / API
PIM Database
• Legacy Application
• Product Information
NoSQL
• REST API
• Product Data
• Additional Metadata

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Now What?
Now What?

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Why multiple languages?
• Sometimes we have no choice
• HTML/CSS/JavaScript + Server Side
• Mobile Native Applications
• Java/.Net are slow movers
• Java EE 5.0 is still mainstream (2006!!)
• Many languages and frameworks
• Scala, Clojure, Groovy, Dart, Go, Ruby, Python, F#, Erlang,
Node.js, Rails, Play!, Grails, ...

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Examples
• Realtime interaction with WebSockets :
• Wait for Java EE 7 to supported by your IT?
• Hack your app server and application with Continuation ?
• Use Node.js and Socket.io ?
• Data Collection and Treatment?
• Find a library?
• Create your library?
• Use Java 8 and Lambdas?
• Use Scala?

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Examples
• Simple CRUD Application
• Use the JavaEE stack with JPA and JSF?
• Use Spring ?
• Use tools like Play!, Grails, Rails, MEAN ?

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How to chose?
• Maturity/Supportability
• Features Set
• Learning Curve
• Productivity

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Use Case : Second Screen Experience
. . .
Node.js + Socket IO
Play! Application
Python Scripts

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Use Case : Recommendation
WebSite / Application
Machine Learning / Recommendation
Data Processing
UserActivity
Application
Data

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Demonstration

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Conclusion
• Use the good tool for the good task
• Do not try to “hack” something when you have a simpler
solution
• Think about your users first... so deliver and get feedback
• Learning is part of our job !
• And this will help you and your project
• What about maintenance?
• Do you think it is easier to maintain complex old code?

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Questions

28. © 2014 MapR Technologies ‹#›© 2014 MapR Technologies
Proud to be Polyglot!
Tugdual Grall
@tgrall
June 11, 2015