Tech Lead, KE Holdings

Application practice of distributed graph database across KE Holdings

This talk answers three core questions: How do you choose the best graph database (one that is ideal for the unique production environment’s needs) from multiple options? How can a knowledge graph with ten billion nodes achieve a millisecond query? How are KE Holdings’s 48 billion ordered triple datasets stored in the database?

Learn why KE Holdings needed a graph database, and then model your selection process on how they chose the right graph database for their business needs. Pan Gao then explains how to deploy the graph database, as well as principles, optimizations, and trade-offs.

By the end of this talk, you’ll know if you need a graph database, how to choose your ideal solution, and what to do to get up and running with Dgraph.

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Founder, Knights Analytics

Building a Centralised Knowledge Graph to Power Your Analytics

A centralized knowledge graph is vital in today’s connected world. In this talk Alex will walk us through how Knights Analytics uses Dgraph to build a knowledge graph in the never ending battle against financial criminals.

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Principal Software Engineer, FactSet

How FactSet used Dgraph and DQL to build a point-in-time model of financial objects

The universe of financial objects includes Countries, Companies, Securities, Stock Exchanges, Indexes, Funds and more. These objects are related in many different ways - and many of these relationships change over time. With this universe loaded into Dgraph, our clients are able to easily explore these relationships as they exist today or at any time in the past.

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CTO, Capventis

Curve Jumping - Dgraph to the front

The recent pandemic has forced a change towards cloud computing and remote working. Customer experiences have changed as have the operational systems and procedures. In order to support these new models, data integrators have to find the best way to move, link and socialise data.

Conventional data stores don’t work well in these environments. However, graph databases provide mechanisms to link and resolve data queries in a much more flexible and cost-effective way.

Mike explains how Capventis uses Dgraph to help with integration - and how Dgraph has reduced development and data management costs.

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Senior Software Engineer, Delhivery

How Dgraph helped in building a model on addresses

In this session I will be talking about efficiently storing and querying a complex and unbounded data of addresses.

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Platform Architect

Customer 360 in Health Analytics

Hailing from a Fortune 100 company, Rachit, the senior platform architect shares with us how the company uses Dgraph to build a Customer 360 platform for the health analytics field. He will go through the criteria required to build a customer 360 system, and why the company chose Dgraph.

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Director/Partner, The Helical Company & Theta Solutions LLC

Badger for Genomics

Rapidly advancing genomic technologies are creating vast quantities of increasingly dense data sources. This data can add significant value across human, plant, and animal applications. However, efficient storage and management of that data can quickly become a burden. To help our clients manage and generate insights from their data, we built a genomic data store and analytics platform on top of BadgerDB - the same database that powers Dgraph.

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Founder & Developer

From SQL to Dgraph, our journey with MissionBase

MissionBase is a small non-profit startup. After growing to over 500 users and implementing advanced ACL we faced challenges and needed to change our tech stack. After struggling to build our own GraphQL implementation, we believed there had to be a better way. We found Dgraph and fell in love.

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Founder, Kin

How Kin uses Dgraph to connect people

Kin is a tool that helps startups find their markets. It is powered in part by Dgraph. This talk will walk through why we chose Dgraph as the tool backing our service.

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Senior Software Engineer, Data Science Group

From zero to hero with Dgraph’s community

In the past year, I have worked on a Github-like system that helps data scientists track and manage their research. Our data looks like a huge graph of branches and versions, so it looked like a graph-based database would be a perfect candidate.

In this talk I will talk about our journey and how the community has helped in our process.

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Senior Full Stack Web Developer

Analytics at scale

In this talk, I will go through the scalability and technical problems that we faced at my company, a Fortune 100 telecommunication company, whose solution required Dgraph. I will share the technical difficulties we faced, and what we did to overcome them.

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