Summary

The Open Data Science Conference brings together a variety of data professionals each year in Boston. This week’s episode consists of a pair of brief interviews conducted on-site at the conference. First up you’ll hear from Andy Eschbacher of Carto. He dscribes some of the complexities inherent to working with geospatial data, how they are handling it, and some of the interesting use cases that they enable for their customers. Next is Todd Blaschka, COO of TigerGraph. He explains how graph databases differ from relational engines, where graph algorithms are useful, and how TigerGraph is built to alow for fast and scalable operation.

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Preamble

Hello and welcome to the Data Engineering Podcast, the show about modern data management

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Your host is Tobias Macey and last week I attended the Open Data Science Conference in Boston and recorded a few brief interviews on-site. In this second part you will hear from Andy Eschbacher of Carto about the challenges of managing geospatial data, as well as Todd Blaschka of TigerGraph about graph databases and how his company has managed to build a fast and scalable platform for graph storage and traversal.

Interview

Andy Eschbacher From Carto

What are the challenges associated with storing geospatial data?

What are some of the common misconceptions that people have about working with geospatial data?

Contact Info

andy-esch on GitHub

@MrEPhysics on Twitter

Website

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

Todd Blaschka From TigerGraph

What are graph databases and how do they differ from relational engines?

What are some of the common difficulties that people have when deling with graph algorithms?

How does data modeling for graph databases differ from relational stores?

Contact Info

LinkedIn

@toddblaschka on Twitter

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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