Graph devroom

Room: H.2214
Calendar: iCal, xCal

	09												10												11												12												13												14												15												16												17												18
Saturday																			Intro to Graph databases								Using graph databases in popular open source CMSs Neo4J and Drupal, potential application areas and module introduction								Incremental Graph Queries with openCypher								Twitter Streaming Graph with Gephi Visualising stream of Data								Bringing the Semantic Web closer to reality PostgreSQL as RDF Graph Database								(Cypher)-[:ON]->(ApacheFlink)<-[:USING]-(Gradoop)								From Shopping Baskets to Structural Patterns								Designing a graph library for JavaScript								Graph Processing on SAP HANA, express edition								Graph Analytics on Massively Parallel Processing Databases								Graphs at scale Scale out Neo4j using Apache Mesos and DC/OS								Network Traffic Analysis of Hadoop Clusters Understand the common usage patterns and identify typical / atypical workloads.

Event		Speakers	Start	End
Saturday
	Intro to Graph databases	Szymon Warda	10:30	11:00
	Using graph databases in popular open source CMSs Neo4J and Drupal, potential application areas and module introduction	Kristof Van Tomme	11:10	11:40
	Incremental Graph Queries with openCypher	Gabor Szarnyas	11:50	12:20
	Twitter Streaming Graph with Gephi Visualising stream of Data	Matthieu Totet	12:30	13:00
	Bringing the Semantic Web closer to reality PostgreSQL as RDF Graph Database	Jimmy Angelakos	13:10	13:40
	(Cypher)-[:ON]->(ApacheFlink)<-[:USING]-(Gradoop)	Martin Junghanns, Max Kießling	13:50	14:20
	From Shopping Baskets to Structural Patterns	André Petermann	14:30	15:00
	Designing a graph library for JavaScript	Guillaume Plique	15:10	15:40
	Graph Processing on SAP HANA, express edition	Thomas Fischer	15:50	16:20
	Graph Analytics on Massively Parallel Processing Databases	Frank McQuillan	16:30	17:00
	Graphs at scale Scale out Neo4j using Apache Mesos and DC/OS	Jörg Schad	17:10	17:40
	Network Traffic Analysis of Hadoop Clusters Understand the common usage patterns and identify typical / atypical workloads.	Mirko Kämpf	17:50	18:15

FOSDEM17