SHOW: 405
DESCRIPTION: Aaron and Brian talk with Emil Eifrem, (@emileifrem, Founder/CTO @Neo4j) about the emergence of graph databases, common use-cases, and how developers are thinking about new ways to leverage graph databases.
SHOW SPONSOR LINKS:
CLOUD NEWS OF THE WEEK:
SHOW INTERVIEW LINKS:
SHOW NOTES:
Topic 1 - Welcome to the show. You’ve been the CEO of Neo4j for over a decade now. How has the landscape around application-usage of data changed in the most significant ways?
Topic 2 - For many decades, most data-centric applications were built around Relational Databases (SQL Databases). These days, application patterns and use-cases have expanded significantly. How do graph databases fit into these new trends?
Topic 3 - With all the new patterns emerging, there are both business reasons and technical reasons for choosing the right database platform. How do you find the business-level thought process happening (contributing, influencing) around platform choice? How do you find the technical-level thought process happening (contributing, influencing) around platform choice?
Topic 4 - Every company that’s involved with the commercialization of open source projects is trying to figure out the best way to manage a portfolio between OSS, software offerings and cloud offerings. How does Neo4j think about that balance?
Topic 5 - Getting developer momentum and mass around a set of patterns is critical. How does Neo4j think about enabling developers, and what are some of the things you’ve done to accelerate their success and consistent learning?
FEEDBACK?
SHOW: 405
DESCRIPTION: Aaron and Brian talk with Emil Eifrem, (@emileifrem, Founder/CTO @Neo4j) about the emergence of graph databases, common use-cases, and how developers are thinking about new ways to leverage graph databases.
SHOW SPONSOR LINKS:
CLOUD NEWS OF THE WEEK:
SHOW INTERVIEW LINKS:
SHOW NOTES:
Topic 1 - Welcome to the show. You’ve been the CEO of Neo4j for over a decade now. How has the landscape around application-usage of data changed in the most significant ways?
Topic 2 - For many decades, most data-centric applications were built around Relational Databases (SQL Databases). These days, application patterns and use-cases have expanded significantly. How do graph databases fit into these new trends?
Topic 3 - With all the new patterns emerging, there are both business reasons and technical reasons for choosing the right database platform. How do you find the business-level thought process happening (contributing, influencing) around platform choice? How do you find the technical-level thought process happening (contributing, influencing) around platform choice?
Topic 4 - Every company that’s involved with the commercialization of open source projects is trying to figure out the best way to manage a portfolio between OSS, software offerings and cloud offerings. How does Neo4j think about that balance?
Topic 5 - Getting developer momentum and mass around a set of patterns is critical. How does Neo4j think about enabling developers, and what are some of the things you’ve done to accelerate their success and consistent learning?
FEEDBACK?