GCP Streaming Architecture: Pub/Sub, Dataflow, and BigQuery
Google Cloud's streaming stack consists of Pub/Sub (messaging), Dataflow (processing, Apache Beam), and BigQuery (analytics with streaming inserts). This guide compares GCP-native streaming with an open-source alternative using RisingWave.
GCP Streaming Stack
Data Sources → Pub/Sub → Dataflow (Beam) → BigQuery / Bigtable
Alternative: Pub/Sub + RisingWave
Data Sources → Pub/Sub → RisingWave → Query via PG + Iceberg sink
| Aspect | GCP Native | RisingWave Alternative |
| Messaging | Pub/Sub | Pub/Sub (same) |
| Processing | Dataflow (Beam) | RisingWave (SQL) |
| Serving | BigQuery/Bigtable | RisingWave (built-in PG) |
| Language | Java/Python (Beam SDK) | SQL only |
| Vendor lock-in | High | Low (open source) |
| Cost | Dataflow + BigQuery | Compute + S3 |
Frequently Asked Questions
Can RisingWave replace Dataflow?
For SQL-expressible streaming workloads, yes. RisingWave provides simpler SQL-based development and built-in serving. For Beam's portable programming model or complex Python/Java transformations, Dataflow remains better.
Does RisingWave work with Pub/Sub?
RisingWave doesn't have a native Pub/Sub connector, but you can bridge Pub/Sub to Kafka using Confluent's connector, then consume from Kafka in RisingWave.
