#DevoxxFR #inmemory in-memory data systems what they can do for you Emmanuel Bernard Galder Zamarreño 

Emmanuel Bernard Galder Zamarreño @emmanuelbernard @galderz 

Data is coming Data is flowing 

Insightful application Observe - collect data Orient - Put in context Decide - select course of action Act - Do it Continuous improvement loop Data services Event stream Data analysis Iterative storage Reasoning, decision models and optimization Execution engine 

In-memory systems an case 

Key foundation key/value store Distributed Elastic Optional schema ASL 2.0 

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in-memory systems in an architecture 

Caching Caching service data Get faster App 1 App 2 Infinispan Datastore 

(derived) Primary store Stateless apps in a stateful universe Microservice “local” storage (Fast) Search capabilities Analytics Distributed tasks App 1 App 2 Infinispan 

Distributed stream Move computation to data map(λ) λ λ 

In action! 

Station board stop station train 

What is the time of the day when there is the biggest ratio of delayed trains? 

Mixing stores Mix traditional datastores and in-memory Temporary data Heavy computation App JPA OGM ORM App JPA OGM ORM App JPA OGM ORM Infinispan RDBMS 

Data virtualisation duct taping Microservice 1 Big old Datasource Dedicated Schema 1 Dedicated Schema 2 Dedicated Schema 3 Data Virtualisation Microservice 2 Microservice 3 Old app 

Analytics and Spark Computation out of Spark Source of data Source of events Immutable RDD Fast RDD caching Spark cluster Infinispan Cassandra Hive RDBMS App 1 

Syncing grids Active / Active Data synced between sites One grid per usage OLTP Analytics App 1 App 2 Infinispan Infinispan Active / active cross site replication Datacenter 1 Datacenter 2 Load balancer 

Pay attention, be reactive Reactive application Reactive microservice Also look at Debezium App 1 “Reactive app” 2 Infinispan Change event “Reactive app” 1 Change event 

Continuous query Reactive to data changes Index the query, not the data from User u where u.age >18 and u.country = ‘France’ from User u where u.age >18 and u.hasSnapshat = true from User u where u.email contains ‘yahoo.com’ { “country”: “France”, “age”: 17, “email”: “[email protected]”, “hasSnapshat”: true } { “country”: “France”, “age”: 19, “email”: “[email protected]”, “hasSnapshat”: true } => 

In action! 

Central Train Delays Dashboard 

Debezium and CDC Change Data Capture Transforms datastores into data change events No change to existing apps and datastores Add features as separate apps Decorrelate event consumers (each at its own pace) 

Data are like Gremlins but good Observe - collect data Orient - Put in context Decide - select course of action Act - Do it Continuous improvement loop 

Thanks http://infinispan.org http://blog.infinispan.org @infinispan DEMOs: https://github.com/ galderz/datagrid-patterns http://debezium.io http://teiid.org Explore your data Take calculated risks Any use case? 

Credits engineer by Wilson Joseph from the Noun Project panel by gira Park from the Noun Project Approve by Aha-Soft from the Noun Project Database sharing by YuguDesign from the Noun Project ram by Andrea Rizzato from the Noun Project Database Search by Nimal Raj from the Noun Project Cloud Analytics by Kevin Augustine LO from the Noun Project Broken Computer by Dan Hetteix from the Noun Project data search by Gregor Črešnar from the Noun Project Server by Creative Stall from the Noun Project Network by Creative Stall from the Noun Project transformation by Felipe Perucho from the Noun Project analytics by Roman Kovbasyuk from the Noun Project Server by Designify.me from the Noun Project