This topic covers the nodes, their responsibilities, and relationships within our product architecture for developers seeking a deeper understanding of RisingWave.
psql
to connect seamlessly
engine=iceberg
, powered by Apache Iceberg table format. Data is stored in a columnar structure to enhance performance for ad hoc OLAP-style queries.CREATE MATERIALIZED VIEW
, it can be changed to its streaming equivalent:
t
receives a DML update like INSERT INTO t VALUES(1)
, this update propagates to m1
. The stream graph for m1
takes the last count, adds 1 to it, and materializes this new count. You can query the latest results from m1
at any time using SELECT * FROM m1
.
EXPLAIN
to see what the execution graph looks like.
Once the execution nodes are built, we trigger historical data backfilling to ensure consistency with upstream sources. After backfilling completes, the streaming job will be created to continuously process upstream data, materialize updates, and propagate the transformed data stream to any downstream systems. See An overview of the RisingWave streaming engine for more information.