Presented by:

Frank mcsherry

Frank McSherry


Frank McSherry is Chief Scientist at Materialize, where he (and others) convert SQL into scale-out, streaming, and interactive dataflows. Before this, he developed the timely and differential dataflow Rust libraries (with colleagues at ETHZ), and led the Naiad research project and co-invented differential privacy while at MSR Silicon Valley. He has a PhD in computer science from the University of Washington.

No video of the event yet, sorry!

As the world moves towards lower latency in operational workloads, a new opportunity is emerging for database architects to ask which query processing work in their database should be performed proactively, as data change, and which work should be performed reactively, as queries roll in. Naturally, to do this you will need a tool that integrates seamlessly with PostgreSQL and maintains your query results for you.

Materialize is a PostgreSQL wire-compatible operational data warehouse that both computes and maintains query results, even as the underlying data change. You can connect it to upstream sources, including PostgreSQL instances, to mirror their data, or use Materialize's own tables directly. You can materialize (almost) any view over these tables, which is then kept always up to date as the tables are updated. Subsequent uses of such views just read results out rather than recompute them, but still provide (strict) serializability. You can even stream out the changelog of any maintained views, to drive alerting or notification.

Explore these concepts with Frank McSherry, co-founder of Materialize, as he unpacks the reasons and process they took in creating a PostgreSQL wire-compatible Operational Data Warehouse.

2024 April 17 10:10 PDT
20 min
Postgres Conference 2024