Understanding Time-Series Database Patterns

SHOW: 394

DESCRIPTION: Brian talks with Evan Kaplan (@evankaplan, CEO of InfluxData) about why companies choose time-series databases, commons use-cases, how time-series patterns align to changing business goals, and how to translate business demands to developer capabilities. 

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CLOUD NEWS OF THE WEEK:

GCP partners with Open-Source CompaniesPentagon narrows JEDI Cloud contract down to AWS and Azure

SHOW INTERVIEW LINKS:

InfluxData Homepage The InfluxData TICK Stack (Telegraf, InfluxDB, Chronograf, Kapacitor)InfluxData closes $60M Round of Funding (Feb 2019)

SHOW NOTES:

Topic 1 - Welcome to the show. You’ve been the CEO of InfluxData for a few years, but please share with the audience your background and how you came to lead InfluxData.

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 time-series 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 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 InfluxData think about that mix, and what are you seeing in terms of customer-demand trends? 

Topic 5 - Getting developer momentum and mass around a set of patterns is critical. How does InfluxData think about enabling developers, and what are some of things you’ve done to accelerate their success and consistent learning? 

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