 Hi, my name is Jeff Denworth, chief marketing officer and co-founder of VASData. VASDataBase is essentially a critical component of the VASData platform and really allows us to apply the contextual or semantic layer into the system such that as we're going and refining data through the data platform and working with this very rich forms of unstructured data, we can now apply a semantic understanding of that data in both transactional context meaning we can receive flows of data in real time but also an analytical context so that we can really go and process on that data and analyze that data in real time as it's flowing through the system. We want to build systems where you can bring your applications to the data and that starts by having open interfaces that enterprises can trust and are familiar with using. We also embrace the idea that we really want to simplify every single aspect of the approach to infrastructure that we're bringing to the table and first getting rid of different complex tiers of data management and also really finding first principle solutions to working with customers on how they most want to work and the simplest ways to deal with their data. And third, as with everything we do, it's really about allowing you to deploy infrastructure on your terms. Your data, the clouds and either public cloud or private cloud that you want to deploy on is entirely of your choosing and with the vast data space now we can stitch all of this together into one unified environment where everything is always under your control. The vast database allows for all of the data in the system to basically be streamed in in real time and also cataloged in real time using the vast database so it's a transactional system first and foremost that's designed to organize your data but it's also analytical in the sense that you can quickly understand everything that's inside of the system. The objective here is to really simplify the way that people do data engineering. We're basically eliminating all of these constraints in a new approach to building databases that we're super excited to introduce today. We wanted to take a step back and first explain how we think about the database management system market. Classically within most organizations you'll find a collection of systems that are designed to deploy and manage tabular data. These systems typically don't scale and for that reason customers then go and build other systems to analyze their data. Now when we started we kind of asked the question why do all these systems exist and if a database was fully featured such that you could scale to any level of proportions and you could query upon the systems that you're also transacting to would we have all of these technologies in the in the market today and that answers probably no but in order to understand how to remove the constraints that have resulted in these different types of systems we wanted to really think about okay why are these different technologies in play today. Customers are largely stuck on hard drives for their large data lakes which really doesn't work for people that want to go and transact into environments using rapid IO IOPS centric operations that are classic with databases and so for this reason you've always had different types of systems in an environment. We wanted to build a system that as data comes in through the different senses files objects tables streams essentially we could go and make realizations upon this data in real time and what we wanted to build was a system that could ingest data at very very high rates of speed in a transactional manner but at the same time query upon that data instantaneously in a real-time data-driven manner and for this reason we needed to invent an all-new approach to database services that we call the VAS database. The VAS database isn't essentially intended to do is to blur the lines between database services data warehouse services data lake services imagine a system that is a system of record but at the same time allows you to query on all of your data instantaneously all the way down to the archive that makes it also a system of insight now it's important to understand that the database starts by building on top of the vast days architecture days stands for disaggregated and shared everything and what we have is a next-generation distributed system where all of the logic runs in standard Linux containers and then over a high speed low latency data center fabric all of the data is presented to all of the machines in parallel and one global volume of low-cost flash really what we've done is we've abstracted a cluster architecture and made essentially a data center scale computer where you just have cores that all have access to the same global volume and that is instrumental to rethinking the whole database paradigm because if you don't have machines that need to coordinate with each other at all in the reader-write path then you can start to build for very very transactional services but at the same time get to unprecedented levels of scale both in terms of capacity and in terms of performance