Company
DataSpren: A Next Generation Data Analytics Platform
Why We Started
Analytical data workloads are probably the most interesting ones we have. It can be all or nothing. There were situations where we expected "weird" randomness but instead the data followed a normal distribution that immediately becomes actionable. And of course there is also the part where nothing made sense and we spent days transforming and fixing the data to even come to this point. Nonetheless, knowing that some part of your business follows a normal distribution makes it actionable and predictable (usage, orders, sales, ... you name it).
We worked with the tools available in our domain, surely not all of them, but the ones we used usually made us question all the time: why didn't they do this, what are these companies doing all day long? They are worth over one billion dollars. Do they even use their own tooling?
Well, some complaints might be unreasonable but we think there is some truth to it after all those years. That's our bet. These data integration and analytical platform providers either miss important functionality or are overly complex instead of having sensible defaults that work for more than 95% of the users. We don't want to replace these platforms but rather create an alternative that is more aligned with the analytical data needs of most businesses (usually not in the petabyte territory of queried data).
At the end of the day:
- Engineers want to: Move, Transform, Visualize, and Govern data easily.
- Business people want to: Gain valuable insights that are actionable.
We can build that!
Our Approach
Not a day goes by where we don't think about our beloved PostgreSQL (even our friends make fun of it). We just love data and the technology that drives it.
We start from first principles, reducing complexity and bloat. We have already figured out a lean architecture that will drive our analytical platform. It allows us to integrate AI in a meaningful and powerful way. Our analytics platform will be the next generation of analytical tooling. We have endless ideas from all the years we have worked in the space.
We are starting with data notebooks as our first product. It is still in development and the first step before we build the full platform. It should support us to connect with the data engineering community.
What We're Building
We are going to build an analytical data platform that lets our users:
- move data reliably with time-travel, replay, fanout, debugging tools, ...
- analyze their data in our analytical database with features like time-travel, ACID, schema evolution, ...
- build actionable dashboards
- connect with existing tooling via PostgreSQL Wire Protocol
We are aware that there are a lot of moving pieces and we don't intend to build them all at once. To mitigate this, we leverage existing software to the full extent. We stay compatible with established standards and interfaces (e.g. PostgreSQL), meaning that basically all existing tooling (e.g. BI tools) will be compatible with our platform right from the start.
Join Us
We are looking for:
- investors who also offer lots of advice
- talented employees in the future who are as excited as we are
Best,
Alexander Netz
Founder of DataSpren