Cloud Computing artwork

Blockchain beyond the Database

Cloud Computing

August 21, 2019 05:00 - 39 minutes - 27 MB - ★★★★ - 79 ratings
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SHOW: 411

DESCRIPTION: Brian talks with Brian Platz (@bplatz, CEO/Co-Founder at @Flureee) about blockchain use-cases outside of cryptocurrencies, immutable data, graph databases, and building APIs on data. 

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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 Ocean[FREE] Try an IT Pro ChallengeGet 20% off VelocityConf passes using discount code CLOUD

CLOUD NEWS OF THE WEEK:

Microsoft acquires JClarityAWS forbids partners from mentioning multi-cloudDoes the VMware buying Pivotal announcement happen this week or during VMworld?

SHOW INTERVIEW LINKS:

Fluree Homepage - Business Application PlatformBrian Platz on Hackernoon [podcast]

SHOW NOTES:

Topic 1 - Welcome to the show. Before we jump into Fluree and the breadth of technologies that power the stack, let’s talk about your background and what drove you to create Fluree. 

Topic 2 - Let’s start with the problems - why does the industry need a new data management stack? What types of use-cases or data-management problems does the Fluree stack address?

Topic 3 - Let’s talk about the Fluree stack, because it brings together several technologies (e.g. Blockchain, GraphQL, etc.) that have gotten a lot of hype, but people aren’t always sure how they should be used.  

Topic 4 - When we step back and look at the Fluree stack, we see a focus around distributed architectures, immutability, graph data richness. Much of this sounds like it aligns to aspects of what is known as the Semantic Web. Are there connections there?

Topic 5 - Let’s talk about your philosophy about API management and exposing data at the data-layer instead of the app-layer. What are the pros and cons of this sort of trade-off, and what are some of the things either data or app teams need to consider with this approach?

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