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EDBT 2011 Uppsala by Mind Map: EDBT 2011 Uppsala
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EDBT 2011 Uppsala






Data Size, Exponential growth, Polarization mobile/cloud

Data Complexity, User generated content, Frequent schema migrations, Sparse data, Targeted analytics, Social graphs, Reasoning and automatic enhancing of information, Dynamic languages

Data Models

KV stores

Bigtable (Column)


GraphDB, Graphs, Data Locality, benefits, Joins made explicit insert-time, Upfront in-graph indicies, Index-free adjacency, Performance index/traversal, Relationship walking linear, RDBMS touches all data, Combination with global edge/relationship indicies, Other approaches, Exchaustive batch processing, BI, Matrix operations, Precomputing, challenges, scaling, Replication/Sharding, Write-scaling: No autosharding for graphs, Insert Time sharding, Domain models, Standard approaches, Runtime sharding, research on sharding functions ongoing, read-scaling, Localized querying mechanisms, Lookup->result set->traversal->crunch, Parallel traversals, Map-reduce style traversals, replicated datasets, independent traversals, Data local modeling of analytical problems, Traversal optimization, Remote traversals, Graph Models, Unlabeled graph, Hypergraph, Property Graph, Data model, Elements, Node (Vertex), Relationship (Edge), Property (Label, Directed, Labeled, Example, Untitled, Performance, Indicies, Domains, Charateristics, Data mostly on Edges, Trees, Hierarchies, Networks, Typical domains, BioInformatics (Susan), Computational Genomics, Bio4J (UniProt, GO, UniRef), PubMed, Food networks, Untitled, Social, Untitled, File systems, configurations, hierachies, Untitled, CMDB, Untitled, MDM, Untitled, Untitled, GIS, Topology Analysis, Geographical Analytics, LBS, FourSquare, Facebook Places, Any domain data mapping, Open Government, INSPIRE, Open Street Map, Untitled, Routing, Untitled, Retail, eCommerce, Workflow scenarios, CMS, ACL, Untitled, Activity Streams, Load balancing in the graph, Querying, Strategy, Lookup->Traverse in graph->lookup, approaches, Callback, Model, TraversalDescription, Evaluator (Pruning, Resultfilter), Order, DepthFirst, BreadFirst, RelationshipExpander, Examples, Untitled, Untitled, Set-based indicies, SQL, Lucene etc, Object traversal from software stacks, Django, Rails, Spring, Query by example, SparQL/RDF, Untitled, Graph Matching approaches, DataFlow, Stacked Iterators, Gremlin, Untitled, Languages, Python, Java, Jruby, Groovy, Scala, Untitled, REST- C#, Python, PHP, Ruby, Untitled, Binary protocol in 1.4, Other Data models mapping, Object Graph Mapping, Node-Object, Inference, Duck-typing, Lazy Migrations, RDF, SQL, Hypergraph mapping, unlabeled graph mapping, Data Local Queries, Defined Traversals, FOAF 2 step, Geographic RTree Search, Local Heuristics, Random Walks, Rodriguez, M.A., Grammar-Based Random Walkers in Semantic Networks, Knowledge-Based Systems, 21(7), pp. 727-739, 2008, Exhaustive Local Algorithms, Dijkstra, A*, Global Heuristics, Page Rank, Indicies on demand, Activity Streams, Analytics, Persistence Models, K/V Store, HypergraphDB, Memory based, R, Redis, Trinity, Object Databases, InfiniteGraph, DB4O, OrientDB, RDBMS Wrappers, Infogrid, FlockDB, Multilinked storage format, Neo4j, Others, Pregel

Thanks to

Emil Eifrem,

Marko Rodriguez, graphy friend

Alex Averbuch, SICS

Pierre Senellart - Invited me

Tore Risch - EDBT 2011 Chairman

Who am I?

Peter Neubauer


OSS projects Graph Database Graph Processing Stack OSGi Java Domain Driven Design



papers on graphs

"The Graph Traversal Pattern" with Marko Rodriguez,

"A Path Algebra for Multi-Relatoinal Graphs" with Marko Rodriguez,