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30 November 2020, 06:00 PM

From databases to platforms: the evolution of Graph databases

A talk by Steven Xi, George Anadiotis, Alan Morrison, Steve Sarsfield and Juan Sequeda
Eastlink Capital Partners, L.P., Knowledge Connexions / Linked Data Orchestration / Year of the Graph / ZDNet, PwC, Independent voice. Formerly of Cambridge Semantics, Vertica, Talend, IBM & data.world

Speaker expertise

Over 25 years of experience as an investor, entrepreneur and investment banker in the U.S. and China -Private Equity/Venture Capital: Riverwood Capital, The Hina Group, China Everbright (Hong Kong), SSB/GSC Partners (Hong Kong) -Investment Banking: Dresdner Kleinwort (Hong Kong), SSB/GSC Partners (Hong Kong), and CSFB (New York) -Entrepreneurship: VanceInfo (NYSE:VIT), and an Ecommerce start-up (eBay model for greater China) Specialties: Private Equity/Venture Capital, Entrepreneurship/Internet/enterprise software, Investment Banking (M&A)


This workshop wants to help answer everything you’ve always wanted to ask about graph databases, but did not have the chance to.

Initially, graph databases were met with skepticism

Not just in terms of what they can do, but even fundamentally, ontologically, in terms of what a graph database is

Some among us pioneered mainstream attention to graph databases

We’d like to think we are past the stage of defining what do we talk about, when we talk about graph databases

Gartner certainly thinks so, as their projection is that:

“The application of graph processing and graph databases will grow at 100% annually through 2022 to continuously accelerate data preparation and enable more-complex and adaptive data science”

We see this happening. To speak in technology adoption terms, we are past the innovators, and well into the early adopters stage

But what about the rest of the world?

The majority of users know about graph databases by now

But they don’t necessarily know all there is to know about them

We want to help fill that gap

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Key Topics

  • Graph database fundamentals
  • Graph database types and use cases
  • Graph database evolution and outlook

Target Audience

  • CxOs
  • Data Scientists
  • Software Engineers
  • Investors

Goals

  • Explore the graph database landscape
  • Answer questions that matter
    • What are graph databases good at, and what are they not so good at
    • Which graph database is a good match for which use case
    • What matters when choosing a graph database
    • What are the pitfalls and barriers to entry
    • How can they be mitigated
    • What are the next milestones / roadblocks

Session outline

  • Introduction
    • Meet and Greet
    • Goals and scope of the tutorial
  • Knowing graph databases
    • What can graph databases do? What are their features and capabilities?
    • Graph database flavors and data models: RDF and property graphs
    • How are graph data models different?
    • What are the strengths and weaknesses of each data model?
  • Using graph databases
    • How do data models relate to use cases?
    • What about usability?
    • What other ways are there to access graph databases other than graph query languages? GraphQL, SQL, visual interfaces, BI tools?
    • What are the strengths and weaknesses of each data model?
  • Choosing a graph database
    • How can users choose a graph database to match their use case?
    • What are some pitfalls to look out for, and how can they be avoided?
  • Conclusions and outlook
    • How is the market evolving?
    • What is the outlook?

Format

  • Extended panel
  • Expert discussion, coordinated by moderator
  • 2 hours running time
  • Running time includes modules of expert discussion, interspersed with modules of audience Q&A / interaction

Level

  • Beginner - Intermediate

Prerequisite Knowledge

  • Basic understanding of graph databases


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