Downloaded 98 times
![Graph Query Language: Cypher
MATCH (:Person { name:“Dan”} ) -[:LOVES]-> (:Person { name:“Ann”} )
LOVES
Dan Ann
NODE NODE
LABEL PROPERTYLABEL PROPERTY](https://image.slidesharecdn.com/graphallthethings-seattle-march52015-150306115847-conversion-gate01/85/Graph-all-the-things-PRathle-19-320.jpg)
![MATCH (boss)-[:MANAGES*0..3]->(sub),
(sub)-[:MANAGES*1..3]->(report)
WHERE boss.name = “John Doe”
RETURN sub.name AS Subordinate,
count(report) AS Total
Express Complex Relationship Queries Easily
Find all direct reports and how
many people they manage,
up to 3 levels down
Cypher Query
SQL Query](https://image.slidesharecdn.com/graphallthethings-seattle-march52015-150306115847-conversion-gate01/85/Graph-all-the-things-PRathle-20-320.jpg)
![(Market) - [:LOVES] - > (Graphs)](https://image.slidesharecdn.com/graphallthethings-seattle-march52015-150306115847-conversion-gate01/85/Graph-all-the-things-PRathle-29-320.jpg)
Uploaded byNeo4j
Graph all the things - PRathle
This document provides an introduction to graph databases and their advantages over relational and NoSQL databases for modeling connected data. It discusses how graph databases can unlock value from data relationships in areas like recommendations, fraud detection, and identity management. The document explains that graph databases allow flexible modeling of nodes and relationships, powerful graph queries, and the ability to easily add new types of data over time. It presents the example of Neo4j as the leading graph database and discusses how early adopters were able to gain competitive advantages through new applications and insights leveraging their connected data in a graph model.
More Related Content
Similar to Graph all the things - PRathle
Graph all the things - PRathle
- 1. Graph All TheThings! Introduction to Graph Database
- 2. What do thesecompanies have in common?
- 3. Realizing Value fromData Relationships in Consumer Web
- 4. Realizing Value fromData Relationships in Consumer Web
- 5. Realizing Value fromData Relationships in Consumer Web
- 6. Ref: http://www.gartner.com/id=2081316 Interest Graph PaymentGraph Intent Graph Mobile Graph Social Graph Gartner: Competitive Dynamics of Consumer Web Five Graphs Deliver a Sustainable Advantage
- 7. High Business Valuein Data Relationships Data is increasing in volume… • New digital processes • More online transactions • New social networks • More devices Using Data Relationships unlocks value • Real-time recommendations • Fraud detection • Master data management • Network and IT operations • Identity and access management • Graph-based search… and is getting more connected Customers, products, processes, devices interact and relate to each other Early adopters became industry leaders
- 8. Unlocking Value fromYour Data Relationships 1. Model your data as a graph of data and relationships 2. Use relationship information in real-time to transform your business 3. Add new relationships on the fly to adapt to your changing business
- 9. Relational DBs Can’tHandle Data Relationships Well • Cannot model or store data and relationships without complexity • Performance degrades with number and levels of relationships, and database size • Query complexity grows with need for JOINs • Adding new types of data and relationships requires schema redesign, increasing time to market … making traditional databases inappropriate when data relationships are valuable in real-time Slow development Poor performance Low scalability Hard to maintain
- 10. NoSQL Databases Don’tHandle Data Relationships • No data structures to model or store relationships • No query constructs to support data relationships • Relating data requires “JOIN logic” in the application • No ACID support for transactions … making NoSQL databases inappropriate when data relationships are valuable in real-time
- 11. Graph Databases –Re-Imagine Your Data as a Graph An enterprise-grade graph database enables you to: • Model and store your data as a graph • Query data relationships with ease and in real-time • Seamlessly evolve applications to support new requirements by adding new kinds of data and relationships Agile development High performance Vertical and horizontal scale Seamless evolution
- 12. “Forrester estimates thatover 25% of enterprises will be using graph databases by 2017” The Graph Database Revolution “Graph analysis is possibly the single most effective competitive differentiator for organizations pursuing data-driven operations and decisions after the design of data capture.” “Neo4j is the current market leader in graph databases.” IT Market Clock for Database Management Systems, 2014 https://www.gartner.com/doc/2852717/it-market-clock-database-management TechRadar™: Enterprise DBMS, Q1 2014 http://www.forrester.com/TechRadar+Enterprise+DBMS+Q1+2014/fulltext/-/E-RES106801 Graph Databases – and Their Potential to Transform How We Capture Interdependencies (Enterprise Management Associates) http://blogs.enterprisemanagement.com/dennisdrogseth/2013/11/06/graph-databasesand-potential-transform-capture-interdependencies/
- 13. Graph Databases –The Fastest Growing DBMS Category Source: http://db-engines.com/en/ranking/graph+dbms 500% increase in popularity over the last 2 years:
- 14.
- 15. Discrete Data Minimally connected data GraphDatabases are designed for data relationships Summary - Use the Right Database for the Right Job Other NoSQL Relational DBMS Graph DB Connected Data Focused on Data Relationships Development Benefits Easy model maintenance Easy query Deployment Benefits Ultra high performance Minimal resource usage
- 16. The Whiteboard ModelIs the Physical Model
- 17. CAR name: “Dan” born: May29, 1970 twitter: “@dan” name: “Ann” born: Dec 5, 1975 since: Jan 10, 2011 brand: “Volvo” model: “V70” Property Graph Model Components Nodes • The objects in the graph • Can have name-value properties • Can be labeled LOVES LOVES LIVES WITH PERSON PERSONRelationships • Relate nodes by type and direction • Can have name-value properties
- 18. Relational Versus GraphModels Relational Model Graph Model KNOWS ANDREAS TOBIAS MICA DELIA Person FriendPerson-Friend ANDREAS DELIA TOBIAS MICA
- 19. Graph Query Language:Cypher MATCH (:Person { name:“Dan”} ) -[:LOVES]-> (:Person { name:“Ann”} ) LOVES Dan Ann NODE NODE LABEL PROPERTYLABEL PROPERTY
- 20. MATCH (boss)-[:MANAGES*0..3]->(sub), (sub)-[:MANAGES*1..3]->(report) WHERE boss.name= “John Doe” RETURN sub.name AS Subordinate, count(report) AS Total Express Complex Relationship Queries Easily Find all direct reports and how many people they manage, up to 3 levels down Cypher Query SQL Query
- 21. Real-Time Query Performance GraphVersus Relational and Other NoSQL Databases Connectedness and Size of Data Set ResponseTime 0 to 2 hops 0 to 3 degrees Thousands of connections Tens to hundreds of hops Thousands of degrees Billions of connections Relational and Other NoSQL Databases Neo4j Neo4j is 1000x faster “Minutes to milliseconds”
- 22.
- 23. Value from DataRelationships Common Use Cases Internal Applications Master Data Management Network and IT Operations Fraud Detection Customer-Facing Applications Real-Time Recommendations Graph-Based Search Identity and Access Management
- 24. Customers Achieve SustainableCompetitive Advantage By Adopting Neo4j New Products & Services Leveraging Data Relationships • First to market, up and running in days, not weeks or months • Reduced churn, increasing engagement and uncovering fraud • Achieved new company vision centered around Business Graph • Leapfrogged the competition with a 360 degree view of the customer Reimagine Existing Applications, and Innovate with Data Relationships • Kept the business running when data growth threatened to stop it • Drastically reduced project complexity and risk • Increased revenue and delighted customers by improving user experience • Brought new offering to market to compete with Amazon Prime & Fresh, and Google Express
- 25. Bringing a GraphDatabase in your Environment
- 26. Data Storage and BusinessRules Execution Data Mining and Aggregation Graph Database Fits into Your Enterprise Environment Application Graph Database Cluster Neo4j Neo4j Neo4j Ad Hoc Analysis Bulk Analytic Infrastructure Hadoop, EDW … Data Scientist End User Databases Relational NoSQL Hadoop
- 27. MIGRATE ALL DATA MIGRATE GRAPH DATA DUPLICATE GRAPHDATA Non-graph data Graph data Graph dataAll data All data Relational Database Graph Database Application Application Application Options for Maintaining Your Data in the Graph
- 28. Quick Start: PlanYour Project 1 2 3 4 5 6 7 8 Learn Neo4j Decide on Architecture Import and Model Data Build Application Test Application All projects vary, but timelines as short as 8 weeks are not unusual PROFESSIONAL SERVICES PLAN
- 29. (Market) - [:LOVES]- > (Graphs)
- 30.
- 31. Users Love Neo4j “Wefound Neo4j to be literally thousands of times faster than our prior MySQL solution, with queries that require 10 to 100 times less code. Today, Neo4j provides eBay with functionality that was previously impossible.” Volker Pacher Senior Developer Horizontal Scaling “The ability to have flexible schema and horizontal scalability is key to our success with Neo4j.” - IT Director, G5000 Professional Services Firm Social Recommendations “Neo4j has allowed us to integrate personalized user experiences—based on our users’ social relationships— into both product and marketing.” - Craig Follett, CEO, Universe True Game Changer “Things that were impossible became possible.” - Markus Paaso, Developer, Sagire Software
- 32. There Are Lotsof Ways to Easily Learn
- 33.
Editor's Notes
- #2 In the near future, many of your apps will be driven by data relationships and not transactions You can unlock value from business relationships with Neo4j
- #7 The consumer web giants derive their competitive advantage from five graphs: "social graph", plus intent, interest, payments and mobile graphs The report concludes with the advice: whatever industry you are in, go and find the graphs that are important to your business, for in them lies a source of “sustainable competitive advantage”. https://www.gartner.com/it/page.jsp?id=2320715 http://www.brettcolbert.me/2013/04/gartner-pcc-ray-valdes-five-graphs.html
- #8 Presenter Notes - Higher Level Value Proposition Everyday, new data is being created at a volume never seen before. And we see that this data is getting even more connected. People communicating as customers, employees, friends, influencers. Customers purchasing products, services or content, expressing their likes and dislikes. Digitization of processes and more data elements for each step. And with Internet of Things (IoT), we have the same thing repeating but with machines talking to each other. There is tremendous value in the knowledge of this relationship information for real-time applications. Examples are Connect a user’s profile and purchases to other users and increase revenue through recommendations for new products and services Reimagine your master data - HR, Customer or Product as a connected model and identify ways to reach customers, improve their experience, identify the best people to staff on projects and more View your individual data elements as part of a process to determine fraud detection or process bottlenecks Companies like Google, LinkedIn and PayPal have done exactly that. Reimagine their data as a network (or a graph) and use the relationship information
- #9 Presenter Notes - How does one take advantage of data relationships for real-time applications? To take advantage of relationships Data needs to be available as a network of connections (or as a graph) Real-time access to relationship information should be available regardless of the size of data set or number and complexity of relationships The graph should be able to accommodate new relationships or modify existing ones
- #10 Presenter Notes - Challenges with current technologies? Database options are not suited to model or store data as a network of relationships Performance degrades with number and levels of relationships making it harder to use for real-time applications Not flexible to add or change relationships in realtime
- #11 Relating data requires building JOIN logic in the application and more data movement over the network
- #12 Presenter Notes - Neo4j - Enterprise Grade Database to re-imagine your data as a Graph Model and store your data as a Graph Traverse any number of or levels of relationships in real-time Evolve the model on the fly
- #23 In the near future, many of your apps will be driven by data relationships and not transactions You can unlock value from business relationships with Neo4j
- #29 It’s easy to learn Neo4j, especially when your team already knows SQL. We partner with you every step of the way in a professional services plan tailored to your needs.
- #34 In the near future, many of your apps will be driven by data relationships and not transactions You can unlock value from business relationships with Neo4j