Whether you're playing around with data in Jupyter, performing ETLs or productionzing your model training pipeline - it is very often the case that you spend more resources on setting up the required infrastructure than performing the actual work.
Getting started with data science at scale can be intimidating. Our experience from working with numerous startups and tech giants led us to this point. We wanted to build something that gets you up and running in 5 minutes, yet confidently scales with you for the foreseeable future.
If you are like us, you appreciate open source software that is easy to use, extendable and easy to maintain. You prefer solutions that give you flexibility, works with other systems and doesn't lock you up in isolated platforms.
This was hard to find - In our quest, we evaluated 20+ data science pipeline solutions, yet none had that special feeling you are looking for. Either it was too hard to get started, slim support for open source distributed computing libraries, or too tightly coupled with a specific cloud providers.
With Sider, we want to change this.