It lets you create materialized views that are automatically updated in an incremental way as underlying data changes, without recomputing the whole query. Previously they supported running those queries on Postgres/Kafka, now they've added their own persistence layer and horizontal scalability.
I have worked at Materialize since 2019. The elevator pitch is that it is a database that lets you maintain the results of queries in memory (and now S3) and have them update in real time so the current result is always available.
Can you describe some use cases? The only one that comes to mind is powering dashboards.
That said, do you support persistent tables or time travel? (E.g., accessing the contents of the view as it was at time t). If not, how should a situation where multiple independent clients read the view be handled? If two people load the same dashboard but see differences based on when the table was read, that might cause confusion.
No, but I think the changes that need to be made in order to do so are tractable, so I expect we will eventually (I’m not an expert in this area of the code, so please don’t take this as an official statement).
I checked the docs but they mention streaming DB, Timely and Differential Dataflow which I don't know either.