<aside> ⚠️ This Pitch Deck is not a solicitation for investment; it is made public for general educational purposes, especially to other startups.
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Computational speed is the backbone of today’s magical user experiences. Jabberwocky achieves industry shattering data speeds through radical data efficiency.
Whereas NVIDIA is easing the congestion at specific repeated-computation bottlenecks with parallel processing via GPUs (graphical processing units), Jabberwocky is easing congestion everywhere else in the data stack with radically efficient data architecture.
https://docs.google.com/presentation/d/1swEiVjwgHnpCS-HUstkNqhPF3cOmGO4KFEIWecQKEgQ/edit?usp=sharing
Why there are so many different categories of databases and data stack services?
The answer is that speed really matters. While perhaps an oversimplification, the core truth is that all of these different products are designed to improve speed for specific use cases, and are therefore incompatible with each other by default.
You may be surprised at just how many categories of data products there are:
Emerging Architectures for Modern Data Infrastructure | Andreessen Horowitz
You may also be surprised at how much inefficiency is introduced when stitching these products and services together. In fact, studies from Google and Microsoft indicate that GPUs can sit idle up to 70% of the time due to data I/O (input/output) bottlenecks.
GPUs Are Fast, I/O is Your Bottleneck | Alluxio
That a step function change in across-the-board efficiency is really possible.
It takes major conviction to continue on a path where application developers, data stack professionals, and even database developers thought there was very little opportunity for gains.