Materialize is a streaming database for real-time applications. Materialize lets you ask questions about your data, and then get low-latency, correct answers, which are kept incrementally updated as the underlying data changes. Materialize is built on Timely Dataflow, a low-latency cyclic dataflow computational model, first introduced in the paper "Naiad: a timely dataflow system".
Materialize is co-founded by Frank McSherry, the primary author of Timely Dataflow (http://timelydataflow.com) and Differential Dataflow (http://differentialdataflow.com), the two open source projects that power Materialize. Materialize itself is source-available and entirely written in Rust: https://github.com/MaterializeInc/materialize
Materialize is a team of around thirty, primarily based in New York City but also open to remote positions in the EU and NA. We are hiring in all engineering positions (eng. manager, engineers from new grad to principal) as well as several non-engineering positions - for the full list, see http://materialize.io/careers
We are a team of significantly experienced individuals in databases and distributed systems, and looking to add more folks with that interest and/or experience to our team. Materialize recently raised a $32m Series B led by Kleiner Perkins, which was lovingly hacker newsed: https://news.ycombinator.com/item?id=25277511