04_Highly Scalable Real-Time Analytics with CloudDBAppliance

1 .Highly Scalable Real-Time Analytics with CloudDBAppliance Boyan Kolev, Oleksandra Levchenko, Florent Masseglia, Reza Akbarina, Esther Pacitti, Patrick Valduriez (INRIA, France) Work partially funded by the EU’s Horizon 2020 programme, grant agreement No. 732051 

2 . Motivation • The cloud today • Cloud data infrastructures fail to provide: • Predictable performance • Support for high loads / strict SLAs • Consequence • Data critical applications still use on-premise mainframe architectures instead of moving to the cloud • The solution • Cloud appliance for providing database-as-a-service with predictable performance, robustness and reliability Work partially funded by the EU’s Horizon 2020 programme, grant agreement No. 732051 2 

3 . Objectives • Innovations • Powerful hardware enabling In-Memory databases • 32TB RAM • 1000+ CPU cores • Vertically scalable in-memory operational database • Vertically scalable in-memory analytics • Vertically scalable real-time streaming analytics • Operational Hadoop data lake • Characteristics • Predictable performance • High availability Work partially funded by the EU’s Horizon 2020 programme, grant agreement No. 732051 3 

4 . High-level Architecture Work partially funded by the EU’s Horizon 2020 programme, grant agreement No. 732051 4 

5 . Real-time Streaming Analytics • Ultra scalable streaming engine • Linear scale-up on many core (1000+) architectures • Algebraic and custom operators to incorporate data mining and machine learning tasks • Time series correlation mining approach • Fast online discovery of correlations over sliding windows of time series data • Massively parallelizable approach • High scalability • Incremental algorithm • Near real-time response • Utilizes in-memory storage • Sharing intermediate data across streaming operators Work partially funded by the EU’s Horizon 2020 programme, grant agreement No. 732051 5 

6 . CloudDBAppliance Use Cases • Validated through five real industrial use application scenarios in three sectors • Finance/Banking • Real-time risk analysis • ATM optimization • Telco • Cell phone number portability • Retail • Proximity marketing • Real-time pricing Work partially funded by the EU’s Horizon 2020 programme, grant agreement No. 732051 6 

7 .Highly Scalable Real-Time Analytics with CloudDBAppliance Thank you! Work partially funded by the EU’s Horizon 2020 programme, grant agreement No. 732051