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  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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  • Stigg | SaaS Monetization and Entitlements API Icon
    Stigg | SaaS Monetization and Entitlements API

    For developers in need of a tool to launch pricing plans faster and build better buying experiences

    A monetization platform is a standalone middleware that sits between your application and your business applications, as part of the modern enterprise billing stack. Stigg unifies all the APIs and abstractions billing and platform engineers had to build and maintain in-house otherwise. Acting as your centralized source of truth, with a highly scalable and flexible entitlements management, rolling out any pricing and packaging change is now a self-service, risk-free, exercise.
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    TRAK Architecture Framework

    TRAK Architecture Framework

    Simple, pragmatic architecture description - for system-thinkers

    TRAK is a general systems-thinkers'/system-centric architecture framework. It is simple, user-friendly, pragmatic and not limited to IT. TRAK has won an INCOSE award and is also a finalist in the 2011 IET innovation awards. TRAK allows you to describe a system, its parts (which can include people, software, other systems and physical things) and how it relates to the residual world. It covers everything from the enterprise, concept, procurement of the solution, the introduction or...
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    dycomodel

    Dynamic Consumption Modeling

    Dynamic Consumption Modeling to create the model of the feature consumption’s flow taking in consideration: the data from prior period of consumption (one time produced) specific model suggested by system and customized by customer everyday/periodically inventory quantity and to predict the remaining quantity of items set the reordering points (first point, with fixed quantity, for fixed dates) GitHub: https://github.com/surban1974/dycomodel
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