Understanding Graph Database Patterns

SHOW: 405DESCRIPTION: 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:Datadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtDigital Ocean HomepageGet Started Now and Get a free $50 Credit on Digital OceanGet 20% off VelocityConf passes using discount code CLOUDCLOUD NEWS OF THE WEEK:IBM closes acquisition of Red Hat ($34B)Cisco acquires Acacia (Optical Networking - $2.6B)Google Cloud acquires Elastifile ($200M)Microsoft and ServiceNow announce strategic partnershipMicrosoft joins hospital chain Providence to build “hospital of the future”SHOW INTERVIEW LINKS:Neo4j HomepageNeo4j Open SourceSHOW 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?Email: show at thecloudcast dot netTwitter: @thecloudcastnet and @ServerlessCastFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @EntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow