SlideShare una empresa de Scribd logo
1 de 18
An overview of InfiniteGraph, the distributed graph database. Darren Wood Chief Architect, InfiniteGraph
For today’s discussion… ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Copyright © InfiniteGraph
Building on Objectivity/DB ,[object Object],[object Object],[object Object],[object Object],[object Object],Copyright © InfiniteGraph
Relationship Analytics Experience ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Copyright © InfiniteGraph
Needed something more… ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Copyright © InfiniteGraph
Enter InfiniteGraph ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Copyright © InfiniteGraph
Some code… Copyright © InfiniteGraph Vertex alice = myGraph.addVertex(new Person(“Alice”));  Vertex bob = myGraph.addVertex(new Person(“Bob”));  Vertex carlos = myGraph.addVertex(new Person(“Carlos”));  Vertex charlie = myGraph.addVertex(new Person(“Charlie”)); alice.addEdge(new Meeting(“Denver”, “5-27-10”), bob); bob.addEdge(new Call(timestamp), carlos); carlos.addEdge(new Payment(100000.00), charlie); bob.addEdge(new Call(timestamp), charlie); Alice Carlos Charlie Bob Meets Calls Pays Calls
Basic Architecture Copyright © InfiniteGraph IG Core/API Configuration Navigation Execution Management Extensions Blueprints User Apps Objectivity/DB Distributed Database Session / TX Management Placement
Copyright © InfiniteGraph
Targeting Large Graphs ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Copyright © InfiniteGraph
Consistency Models ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Copyright © InfiniteGraph
Pipelining Copyright © InfiniteGraph IG Core/API Configuration Navigation Execution Management Extensions Session / TX Management Placement (MDP) Placement (Pipelining) V 1 V 2 V 3 E 12 E 23 Pipeline Manager Staging Containers Pipeline Containers E(1->2) E(3->1) E(2->3) E(2->1) E(2->3) E(3->1) E(1->2) E(3->2) E(1->2) E(2->3) E(3->1) E(2->1) E(2->3) E(3->1) E(3->2) E(1->2)
Distributing Navigation ,[object Object],[object Object],[object Object],Copyright © InfiniteGraph Alice Carlos Charlie Bob Meets Calls Pays Dave Eve Chuck Calls Lives With Meets
Partitioned Graphs are Ugly Copyright © InfiniteGraph Distributed API Application(s) Partition 1 Partition 3 Partition 2 Partition ... n Processor Processor Processor Processor
Making it scale… ,[object Object],[object Object],[object Object],[object Object],Copyright © InfiniteGraph
Flexible Data Models ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Copyright © InfiniteGraph
Other Projects ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Copyright © InfiniteGraph
Thank you ! Copyright © InfiniteGraph [email_address] Twitter - @infinitegraph

Más contenido relacionado

La actualidad más candente

"You don't need a bigger boat": serverless MLOps for reasonable companies
"You don't need a bigger boat": serverless MLOps for reasonable companies"You don't need a bigger boat": serverless MLOps for reasonable companies
"You don't need a bigger boat": serverless MLOps for reasonable companiesData Science Milan
 
Vertex AI: Pipelines for your MLOps workflows
Vertex AI: Pipelines for your MLOps workflowsVertex AI: Pipelines for your MLOps workflows
Vertex AI: Pipelines for your MLOps workflowsMárton Kodok
 
Graph Analytics for big data
Graph Analytics for big dataGraph Analytics for big data
Graph Analytics for big dataSigmoid
 
Using Graph Algorithms For Advanced Analytics - Part 4 Similarity 30 graph al...
Using Graph Algorithms For Advanced Analytics - Part 4 Similarity 30 graph al...Using Graph Algorithms For Advanced Analytics - Part 4 Similarity 30 graph al...
Using Graph Algorithms For Advanced Analytics - Part 4 Similarity 30 graph al...TigerGraph
 
AI Solutions with Macnica.ai - AI Expo 2018 Tokyo Japan
AI Solutions with Macnica.ai - AI Expo 2018 Tokyo JapanAI Solutions with Macnica.ai - AI Expo 2018 Tokyo Japan
AI Solutions with Macnica.ai - AI Expo 2018 Tokyo JapanAvkash Chauhan
 
Using Neo4j and Machine Learning to Create a Decision Engine, CluedIn
Using Neo4j and Machine Learning  to Create a Decision Engine, CluedInUsing Neo4j and Machine Learning  to Create a Decision Engine, CluedIn
Using Neo4j and Machine Learning to Create a Decision Engine, CluedInNeo4j
 
Build a car with Graphs, Fabien Batejat, Volvo Cars
Build a car with Graphs, Fabien Batejat, Volvo CarsBuild a car with Graphs, Fabien Batejat, Volvo Cars
Build a car with Graphs, Fabien Batejat, Volvo CarsNeo4j
 
OracleCode_Berlin_Jun2018_AnalyzeBitcoinTransactionDataUsingAsGraph
OracleCode_Berlin_Jun2018_AnalyzeBitcoinTransactionDataUsingAsGraphOracleCode_Berlin_Jun2018_AnalyzeBitcoinTransactionDataUsingAsGraph
OracleCode_Berlin_Jun2018_AnalyzeBitcoinTransactionDataUsingAsGraphKarin Patenge
 
Domain driven design: a gentle introduction
Domain driven design:  a gentle introductionDomain driven design:  a gentle introduction
Domain driven design: a gentle introductionAsher Sterkin
 
Bridging the Gap Between Datasets and DataFrames
Bridging the Gap Between Datasets and DataFramesBridging the Gap Between Datasets and DataFrames
Bridging the Gap Between Datasets and DataFramesDatabricks
 
When Graphs Meet Machine Learning
When Graphs Meet Machine LearningWhen Graphs Meet Machine Learning
When Graphs Meet Machine LearningJean Ihm
 
No REST till Production – Building and Deploying 9 Models to Production in 3 ...
No REST till Production – Building and Deploying 9 Models to Production in 3 ...No REST till Production – Building and Deploying 9 Models to Production in 3 ...
No REST till Production – Building and Deploying 9 Models to Production in 3 ...Databricks
 
TensorFlow 16: Building a Data Science Platform
TensorFlow 16: Building a Data Science Platform TensorFlow 16: Building a Data Science Platform
TensorFlow 16: Building a Data Science Platform Seldon
 
Automate your Machine Learning
Automate your Machine LearningAutomate your Machine Learning
Automate your Machine LearningAjit Ananthram
 
The More the Merrier: Scaling Model Building Infrastructure at Zendesk
The More the Merrier: Scaling Model Building Infrastructure at ZendeskThe More the Merrier: Scaling Model Building Infrastructure at Zendesk
The More the Merrier: Scaling Model Building Infrastructure at ZendeskDatabricks
 
An introduction to Machine Learning with scikit-learn (October 2018)
An introduction to Machine Learning with scikit-learn (October 2018)An introduction to Machine Learning with scikit-learn (October 2018)
An introduction to Machine Learning with scikit-learn (October 2018)Julien SIMON
 
Big Analytics Without Big Hassles
Big Analytics Without Big HasslesBig Analytics Without Big Hassles
Big Analytics Without Big HasslesParadigm4
 

La actualidad más candente (20)

Machine Learning with Apache Spark
Machine Learning with Apache SparkMachine Learning with Apache Spark
Machine Learning with Apache Spark
 
"You don't need a bigger boat": serverless MLOps for reasonable companies
"You don't need a bigger boat": serverless MLOps for reasonable companies"You don't need a bigger boat": serverless MLOps for reasonable companies
"You don't need a bigger boat": serverless MLOps for reasonable companies
 
AI as a service
AI as a serviceAI as a service
AI as a service
 
Vertex AI: Pipelines for your MLOps workflows
Vertex AI: Pipelines for your MLOps workflowsVertex AI: Pipelines for your MLOps workflows
Vertex AI: Pipelines for your MLOps workflows
 
Graph Analytics for big data
Graph Analytics for big dataGraph Analytics for big data
Graph Analytics for big data
 
Using Graph Algorithms For Advanced Analytics - Part 4 Similarity 30 graph al...
Using Graph Algorithms For Advanced Analytics - Part 4 Similarity 30 graph al...Using Graph Algorithms For Advanced Analytics - Part 4 Similarity 30 graph al...
Using Graph Algorithms For Advanced Analytics - Part 4 Similarity 30 graph al...
 
AI Solutions with Macnica.ai - AI Expo 2018 Tokyo Japan
AI Solutions with Macnica.ai - AI Expo 2018 Tokyo JapanAI Solutions with Macnica.ai - AI Expo 2018 Tokyo Japan
AI Solutions with Macnica.ai - AI Expo 2018 Tokyo Japan
 
Using Neo4j and Machine Learning to Create a Decision Engine, CluedIn
Using Neo4j and Machine Learning  to Create a Decision Engine, CluedInUsing Neo4j and Machine Learning  to Create a Decision Engine, CluedIn
Using Neo4j and Machine Learning to Create a Decision Engine, CluedIn
 
Build a car with Graphs, Fabien Batejat, Volvo Cars
Build a car with Graphs, Fabien Batejat, Volvo CarsBuild a car with Graphs, Fabien Batejat, Volvo Cars
Build a car with Graphs, Fabien Batejat, Volvo Cars
 
OracleCode_Berlin_Jun2018_AnalyzeBitcoinTransactionDataUsingAsGraph
OracleCode_Berlin_Jun2018_AnalyzeBitcoinTransactionDataUsingAsGraphOracleCode_Berlin_Jun2018_AnalyzeBitcoinTransactionDataUsingAsGraph
OracleCode_Berlin_Jun2018_AnalyzeBitcoinTransactionDataUsingAsGraph
 
Introduction to RDF*
Introduction to RDF*Introduction to RDF*
Introduction to RDF*
 
Domain driven design: a gentle introduction
Domain driven design:  a gentle introductionDomain driven design:  a gentle introduction
Domain driven design: a gentle introduction
 
Bridging the Gap Between Datasets and DataFrames
Bridging the Gap Between Datasets and DataFramesBridging the Gap Between Datasets and DataFrames
Bridging the Gap Between Datasets and DataFrames
 
When Graphs Meet Machine Learning
When Graphs Meet Machine LearningWhen Graphs Meet Machine Learning
When Graphs Meet Machine Learning
 
No REST till Production – Building and Deploying 9 Models to Production in 3 ...
No REST till Production – Building and Deploying 9 Models to Production in 3 ...No REST till Production – Building and Deploying 9 Models to Production in 3 ...
No REST till Production – Building and Deploying 9 Models to Production in 3 ...
 
TensorFlow 16: Building a Data Science Platform
TensorFlow 16: Building a Data Science Platform TensorFlow 16: Building a Data Science Platform
TensorFlow 16: Building a Data Science Platform
 
Automate your Machine Learning
Automate your Machine LearningAutomate your Machine Learning
Automate your Machine Learning
 
The More the Merrier: Scaling Model Building Infrastructure at Zendesk
The More the Merrier: Scaling Model Building Infrastructure at ZendeskThe More the Merrier: Scaling Model Building Infrastructure at Zendesk
The More the Merrier: Scaling Model Building Infrastructure at Zendesk
 
An introduction to Machine Learning with scikit-learn (October 2018)
An introduction to Machine Learning with scikit-learn (October 2018)An introduction to Machine Learning with scikit-learn (October 2018)
An introduction to Machine Learning with scikit-learn (October 2018)
 
Big Analytics Without Big Hassles
Big Analytics Without Big HasslesBig Analytics Without Big Hassles
Big Analytics Without Big Hassles
 

Destacado

Workshop Weblog, Wiki & Twitter
Workshop Weblog, Wiki & TwitterWorkshop Weblog, Wiki & Twitter
Workshop Weblog, Wiki & TwitterGSlotboom
 
Colorado Climate
Colorado ClimateColorado Climate
Colorado Climatextina44
 
Greenwich IATA Presentation 7 Oct 2008 Final Website
Greenwich IATA Presentation 7 Oct 2008 Final WebsiteGreenwich IATA Presentation 7 Oct 2008 Final Website
Greenwich IATA Presentation 7 Oct 2008 Final Websitercsmuk
 
Reaching More Customers in 2015 With a Responsive Mobile Website Design
Reaching More Customers in 2015 With a Responsive Mobile Website DesignReaching More Customers in 2015 With a Responsive Mobile Website Design
Reaching More Customers in 2015 With a Responsive Mobile Website DesignRichard Sink
 
About Robyn
About RobynAbout Robyn
About RobynRLNY11
 
Jacl Thurston talk at e-Democracy Conference
Jacl Thurston talk at e-Democracy ConferenceJacl Thurston talk at e-Democracy Conference
Jacl Thurston talk at e-Democracy Conferencejackthur
 
E-learning: Ενίσχυση & Κινητοποίηση των μαθητών στα Μαθηματικά Β΄ Γυμνασίου
E-learning: Ενίσχυση & Κινητοποίηση των μαθητών στα Μαθηματικά Β΄ ΓυμνασίουE-learning: Ενίσχυση & Κινητοποίηση των μαθητών στα Μαθηματικά Β΄ Γυμνασίου
E-learning: Ενίσχυση & Κινητοποίηση των μαθητών στα Μαθηματικά Β΄ ΓυμνασίουLiana Lignou
 
50 Words Powerpoint Brock
50 Words Powerpoint Brock50 Words Powerpoint Brock
50 Words Powerpoint Brockmrrobbo
 
2009 03 31 Healthstory Webinar Presentation
2009 03 31 Healthstory Webinar Presentation2009 03 31 Healthstory Webinar Presentation
2009 03 31 Healthstory Webinar PresentationNick van Terheyden
 
Validazione del Progetto Opere Pubbliche Russo
Validazione del Progetto Opere Pubbliche RussoValidazione del Progetto Opere Pubbliche Russo
Validazione del Progetto Opere Pubbliche RussoEugenio Agnello
 
CORSO TECNICO: “IL SOLARE TERMICO: TEORIA E ASPETTI APPLICATIVI"
CORSO TECNICO: “IL SOLARE TERMICO: TEORIA E ASPETTI APPLICATIVI"CORSO TECNICO: “IL SOLARE TERMICO: TEORIA E ASPETTI APPLICATIVI"
CORSO TECNICO: “IL SOLARE TERMICO: TEORIA E ASPETTI APPLICATIVI"Eugenio Agnello
 
Strategic Energy Systems Planning under Uncertainty
Strategic Energy Systems Planning under UncertaintyStrategic Energy Systems Planning under Uncertainty
Strategic Energy Systems Planning under UncertaintyEmilio L. Cano
 
Leadership In Times Of Uncertainty (2008 10)
Leadership In Times Of Uncertainty (2008 10)Leadership In Times Of Uncertainty (2008 10)
Leadership In Times Of Uncertainty (2008 10)pearsoca
 
GANG Announcements, Sept 2009
GANG Announcements, Sept 2009GANG Announcements, Sept 2009
GANG Announcements, Sept 2009David Giard
 

Destacado (20)

Workshop Weblog, Wiki & Twitter
Workshop Weblog, Wiki & TwitterWorkshop Weblog, Wiki & Twitter
Workshop Weblog, Wiki & Twitter
 
Real grade survey
Real grade surveyReal grade survey
Real grade survey
 
Colorado Climate
Colorado ClimateColorado Climate
Colorado Climate
 
μάθηση
μάθησημάθηση
μάθηση
 
Greenwich IATA Presentation 7 Oct 2008 Final Website
Greenwich IATA Presentation 7 Oct 2008 Final WebsiteGreenwich IATA Presentation 7 Oct 2008 Final Website
Greenwich IATA Presentation 7 Oct 2008 Final Website
 
test
testtest
test
 
Reaching More Customers in 2015 With a Responsive Mobile Website Design
Reaching More Customers in 2015 With a Responsive Mobile Website DesignReaching More Customers in 2015 With a Responsive Mobile Website Design
Reaching More Customers in 2015 With a Responsive Mobile Website Design
 
About Robyn
About RobynAbout Robyn
About Robyn
 
Jacl Thurston talk at e-Democracy Conference
Jacl Thurston talk at e-Democracy ConferenceJacl Thurston talk at e-Democracy Conference
Jacl Thurston talk at e-Democracy Conference
 
E-learning: Ενίσχυση & Κινητοποίηση των μαθητών στα Μαθηματικά Β΄ Γυμνασίου
E-learning: Ενίσχυση & Κινητοποίηση των μαθητών στα Μαθηματικά Β΄ ΓυμνασίουE-learning: Ενίσχυση & Κινητοποίηση των μαθητών στα Μαθηματικά Β΄ Γυμνασίου
E-learning: Ενίσχυση & Κινητοποίηση των μαθητών στα Μαθηματικά Β΄ Γυμνασίου
 
50 Words Powerpoint Brock
50 Words Powerpoint Brock50 Words Powerpoint Brock
50 Words Powerpoint Brock
 
Calling Watson to Ward 8 Stat
Calling Watson to Ward 8 StatCalling Watson to Ward 8 Stat
Calling Watson to Ward 8 Stat
 
2009 03 31 Healthstory Webinar Presentation
2009 03 31 Healthstory Webinar Presentation2009 03 31 Healthstory Webinar Presentation
2009 03 31 Healthstory Webinar Presentation
 
Validazione del Progetto Opere Pubbliche Russo
Validazione del Progetto Opere Pubbliche RussoValidazione del Progetto Opere Pubbliche Russo
Validazione del Progetto Opere Pubbliche Russo
 
Template-devil
Template-devilTemplate-devil
Template-devil
 
Ordenagailu Zatiak
Ordenagailu ZatiakOrdenagailu Zatiak
Ordenagailu Zatiak
 
CORSO TECNICO: “IL SOLARE TERMICO: TEORIA E ASPETTI APPLICATIVI"
CORSO TECNICO: “IL SOLARE TERMICO: TEORIA E ASPETTI APPLICATIVI"CORSO TECNICO: “IL SOLARE TERMICO: TEORIA E ASPETTI APPLICATIVI"
CORSO TECNICO: “IL SOLARE TERMICO: TEORIA E ASPETTI APPLICATIVI"
 
Strategic Energy Systems Planning under Uncertainty
Strategic Energy Systems Planning under UncertaintyStrategic Energy Systems Planning under Uncertainty
Strategic Energy Systems Planning under Uncertainty
 
Leadership In Times Of Uncertainty (2008 10)
Leadership In Times Of Uncertainty (2008 10)Leadership In Times Of Uncertainty (2008 10)
Leadership In Times Of Uncertainty (2008 10)
 
GANG Announcements, Sept 2009
GANG Announcements, Sept 2009GANG Announcements, Sept 2009
GANG Announcements, Sept 2009
 

Similar a InfiniteGraph

Meetup: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.
Meetup: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.Meetup: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.
Meetup: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.InfiniteGraph
 
Fishing Graphs in a Hadoop Data Lake
Fishing Graphs in a Hadoop Data LakeFishing Graphs in a Hadoop Data Lake
Fishing Graphs in a Hadoop Data LakeArangoDB Database
 
Webinar: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.
Webinar: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.Webinar: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.
Webinar: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.InfiniteGraph
 
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and Spark
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and SparkVital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and Spark
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and SparkVital.AI
 
"Building Data Warehouse with Google Cloud Platform", Artem Nikulchenko
"Building Data Warehouse with Google Cloud Platform",  Artem Nikulchenko"Building Data Warehouse with Google Cloud Platform",  Artem Nikulchenko
"Building Data Warehouse with Google Cloud Platform", Artem NikulchenkoFwdays
 
Fishing Graphs in a Hadoop Data Lake by Jörg Schad and Max Neunhoeffer at Big...
Fishing Graphs in a Hadoop Data Lake by Jörg Schad and Max Neunhoeffer at Big...Fishing Graphs in a Hadoop Data Lake by Jörg Schad and Max Neunhoeffer at Big...
Fishing Graphs in a Hadoop Data Lake by Jörg Schad and Max Neunhoeffer at Big...Big Data Spain
 
Rounds analytics pipeline
Rounds analytics pipelineRounds analytics pipeline
Rounds analytics pipelineAviv Laufer
 
Building with AWS Databases: Match Your Workload to the Right Database (DAT30...
Building with AWS Databases: Match Your Workload to the Right Database (DAT30...Building with AWS Databases: Match Your Workload to the Right Database (DAT30...
Building with AWS Databases: Match Your Workload to the Right Database (DAT30...Amazon Web Services
 
Webinar: The Modern Streaming Data Stack with Kinetica & StreamSets
Webinar: The Modern Streaming Data Stack with Kinetica & StreamSetsWebinar: The Modern Streaming Data Stack with Kinetica & StreamSets
Webinar: The Modern Streaming Data Stack with Kinetica & StreamSetsKinetica
 
HBaseConAsia2018: Track2-5: JanusGraph-Distributed graph database with HBase
HBaseConAsia2018: Track2-5: JanusGraph-Distributed graph database with HBaseHBaseConAsia2018: Track2-5: JanusGraph-Distributed graph database with HBase
HBaseConAsia2018: Track2-5: JanusGraph-Distributed graph database with HBaseMichael Stack
 
Introduction to MapReduce Data Transformations
Introduction to MapReduce Data TransformationsIntroduction to MapReduce Data Transformations
Introduction to MapReduce Data Transformationsswooledge
 
Family tree of data – provenance and neo4j
Family tree of data – provenance and neo4jFamily tree of data – provenance and neo4j
Family tree of data – provenance and neo4jM. David Allen
 
How Graph Databases used in Police Department?
How Graph Databases used in Police Department?How Graph Databases used in Police Department?
How Graph Databases used in Police Department?Samet KILICTAS
 
Big Data - HDInsight and Power BI
Big Data - HDInsight and Power BIBig Data - HDInsight and Power BI
Big Data - HDInsight and Power BIPrasad Prabhu (PP)
 
Octo and the DevSecOps Evolution at Oracle by Ian Van Hoven
Octo and the DevSecOps Evolution at Oracle by Ian Van HovenOcto and the DevSecOps Evolution at Oracle by Ian Van Hoven
Octo and the DevSecOps Evolution at Oracle by Ian Van HovenInfluxData
 
Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It! Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It! Cécile Poyet
 
Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It! Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It! Hortonworks
 
Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It! Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It! Cécile Poyet
 

Similar a InfiniteGraph (20)

Meetup: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.
Meetup: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.Meetup: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.
Meetup: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.
 
Fishing Graphs in a Hadoop Data Lake
Fishing Graphs in a Hadoop Data LakeFishing Graphs in a Hadoop Data Lake
Fishing Graphs in a Hadoop Data Lake
 
Webinar: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.
Webinar: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.Webinar: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.
Webinar: An Introduction to InfiniteGraph, and Connecting the Dots in Big Data.
 
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and Spark
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and SparkVital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and Spark
Vital AI MetaQL: Queries Across NoSQL, SQL, Sparql, and Spark
 
Fishing Graphs in a Hadoop Data Lake
Fishing Graphs in a Hadoop Data Lake Fishing Graphs in a Hadoop Data Lake
Fishing Graphs in a Hadoop Data Lake
 
"Building Data Warehouse with Google Cloud Platform", Artem Nikulchenko
"Building Data Warehouse with Google Cloud Platform",  Artem Nikulchenko"Building Data Warehouse with Google Cloud Platform",  Artem Nikulchenko
"Building Data Warehouse with Google Cloud Platform", Artem Nikulchenko
 
Fishing Graphs in a Hadoop Data Lake by Jörg Schad and Max Neunhoeffer at Big...
Fishing Graphs in a Hadoop Data Lake by Jörg Schad and Max Neunhoeffer at Big...Fishing Graphs in a Hadoop Data Lake by Jörg Schad and Max Neunhoeffer at Big...
Fishing Graphs in a Hadoop Data Lake by Jörg Schad and Max Neunhoeffer at Big...
 
Rounds analytics pipeline
Rounds analytics pipelineRounds analytics pipeline
Rounds analytics pipeline
 
Dev381.Pp
Dev381.PpDev381.Pp
Dev381.Pp
 
Building with AWS Databases: Match Your Workload to the Right Database (DAT30...
Building with AWS Databases: Match Your Workload to the Right Database (DAT30...Building with AWS Databases: Match Your Workload to the Right Database (DAT30...
Building with AWS Databases: Match Your Workload to the Right Database (DAT30...
 
Webinar: The Modern Streaming Data Stack with Kinetica & StreamSets
Webinar: The Modern Streaming Data Stack with Kinetica & StreamSetsWebinar: The Modern Streaming Data Stack with Kinetica & StreamSets
Webinar: The Modern Streaming Data Stack with Kinetica & StreamSets
 
HBaseConAsia2018: Track2-5: JanusGraph-Distributed graph database with HBase
HBaseConAsia2018: Track2-5: JanusGraph-Distributed graph database with HBaseHBaseConAsia2018: Track2-5: JanusGraph-Distributed graph database with HBase
HBaseConAsia2018: Track2-5: JanusGraph-Distributed graph database with HBase
 
Introduction to MapReduce Data Transformations
Introduction to MapReduce Data TransformationsIntroduction to MapReduce Data Transformations
Introduction to MapReduce Data Transformations
 
Family tree of data – provenance and neo4j
Family tree of data – provenance and neo4jFamily tree of data – provenance and neo4j
Family tree of data – provenance and neo4j
 
How Graph Databases used in Police Department?
How Graph Databases used in Police Department?How Graph Databases used in Police Department?
How Graph Databases used in Police Department?
 
Big Data - HDInsight and Power BI
Big Data - HDInsight and Power BIBig Data - HDInsight and Power BI
Big Data - HDInsight and Power BI
 
Octo and the DevSecOps Evolution at Oracle by Ian Van Hoven
Octo and the DevSecOps Evolution at Oracle by Ian Van HovenOcto and the DevSecOps Evolution at Oracle by Ian Van Hoven
Octo and the DevSecOps Evolution at Oracle by Ian Van Hoven
 
Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It! Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It!
 
Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It! Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It!
 
Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It! Boost Performance with Scala – Learn From Those Who’ve Done It!
Boost Performance with Scala – Learn From Those Who’ve Done It!
 

Más de University of New South Wales (11)

Declarative analysis of noisy information networks
Declarative analysis of noisy information networksDeclarative analysis of noisy information networks
Declarative analysis of noisy information networks
 
Gremlin
Gremlin Gremlin
Gremlin
 
DHHT - Modeling beyond plain graphs
DHHT - Modeling beyond plain graphsDHHT - Modeling beyond plain graphs
DHHT - Modeling beyond plain graphs
 
Dex
DexDex
Dex
 
Ontological Conjunctive Query Answering over Large Knowledge Bases
Ontological Conjunctive Query Answering over Large Knowledge BasesOntological Conjunctive Query Answering over Large Knowledge Bases
Ontological Conjunctive Query Answering over Large Knowledge Bases
 
Key-Key-Value Stores for Efficiently Processing Graph Data in the Cloud
Key-Key-Value Stores for Efficiently Processing Graph Data in the CloudKey-Key-Value Stores for Efficiently Processing Graph Data in the Cloud
Key-Key-Value Stores for Efficiently Processing Graph Data in the Cloud
 
Allegograph
AllegographAllegograph
Allegograph
 
Neo4j
Neo4jNeo4j
Neo4j
 
Dependable Cardinality Forecast for XQuery
Dependable Cardinality Forecast for XQueryDependable Cardinality Forecast for XQuery
Dependable Cardinality Forecast for XQuery
 
GraphREL: A Relational Graph Query Processor
GraphREL: A Relational Graph Query ProcessorGraphREL: A Relational Graph Query Processor
GraphREL: A Relational Graph Query Processor
 
XML Compression Benchmark
XML Compression BenchmarkXML Compression Benchmark
XML Compression Benchmark
 

InfiniteGraph

  • 1. An overview of InfiniteGraph, the distributed graph database. Darren Wood Chief Architect, InfiniteGraph
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7. Some code… Copyright © InfiniteGraph Vertex alice = myGraph.addVertex(new Person(“Alice”)); Vertex bob = myGraph.addVertex(new Person(“Bob”)); Vertex carlos = myGraph.addVertex(new Person(“Carlos”)); Vertex charlie = myGraph.addVertex(new Person(“Charlie”)); alice.addEdge(new Meeting(“Denver”, “5-27-10”), bob); bob.addEdge(new Call(timestamp), carlos); carlos.addEdge(new Payment(100000.00), charlie); bob.addEdge(new Call(timestamp), charlie); Alice Carlos Charlie Bob Meets Calls Pays Calls
  • 8. Basic Architecture Copyright © InfiniteGraph IG Core/API Configuration Navigation Execution Management Extensions Blueprints User Apps Objectivity/DB Distributed Database Session / TX Management Placement
  • 10.
  • 11.
  • 12. Pipelining Copyright © InfiniteGraph IG Core/API Configuration Navigation Execution Management Extensions Session / TX Management Placement (MDP) Placement (Pipelining) V 1 V 2 V 3 E 12 E 23 Pipeline Manager Staging Containers Pipeline Containers E(1->2) E(3->1) E(2->3) E(2->1) E(2->3) E(3->1) E(1->2) E(3->2) E(1->2) E(2->3) E(3->1) E(2->1) E(2->3) E(3->1) E(3->2) E(1->2)
  • 13.
  • 14. Partitioned Graphs are Ugly Copyright © InfiniteGraph Distributed API Application(s) Partition 1 Partition 3 Partition 2 Partition ... n Processor Processor Processor Processor
  • 15.
  • 16.
  • 17.
  • 18. Thank you ! Copyright © InfiniteGraph [email_address] Twitter - @infinitegraph