Without Refactoring

Supports all languages and stacks

A fluid system of rights and permissions

An environment that can launch anywhere

All stages of development from a single app

Ready to use architectural Back-end framework.

A Ready Storage and Data Management Environment

Business logic and scripting in a single place

Operational environment

Blurring the line between your desktop and your mind-space

Imagine an abstract space in which, at first, only actions with links are possible. With Deep.Case you can be immersed in the data as if it's an extension of your own thoughts. Anchor links around you and configure their behavior. Deep.Case can be utilized by analysts as a data workspace or as a space for assembly. Project management and status monitoring are also viable options. This is an extendable environment built on d3/threejs/AFrame.

On one hand, Deep is a system that embodies the idea of Data Driven Development because it is built upon an associative data space. At the same time, the data is split into atomic elements and is represented as a minimal unit of essence - the associative link. This allows to depict any semantic, logical and abstract constructs in a single dialect for memory operations. Instead of creating a perfect language or a perfect database, Deep is an ideal associative environment with an interchangeable core. This means that it can contain a multitude of competing implementations of databases and API access languages.

A brand-new programming paradigm

We have built a Meta language free of semantic predisposition

Any and all languages and stacks

You can write your ExecutionProvider for any programming language

In Deep the code is stored in Links is capable of processing data events. For instance, it is possible to process events triggered by Links of a certain type as well as utilizing strict selectors from an array of trees via a WHERE-like syntax with support of join and/or traverse mechanics. The code can be written in any language compatible with any ExecutionProvider which is available as the DockerImage for our standard GQL API. And the code will be launched in its DockerImage that is linked to this ExecutionProvider in the database. Official in-transaction handler support will be added soon, as well as systems that will enable to run code on remote devices, including microcontrollers.

No longer are you forced to describe the business logic and restrictions with code. Now you can just define only the operation symbols you need, attach a subject-object-action system using a where-like syntax that will analyze the context upon completing an operation or a rights check. You will always know if there are rules allowing the execution of a single action or any operation using a GQL inquiry. This will keep business logic completely separate from coding decisions.