Lambda vs Kappa Architecture: Which Is Better in 2026?

Data mesh decentralizes data ownership — each domain team owns, produces, and maintains their data products. Stream processing makes data mesh real-time: domain teams publish streaming data products as materialized views that other teams consume via PostgreSQL protocol.

Streaming Data Products

-- Payment team's data product
CREATE MATERIALIZED VIEW payments_data_product AS
SELECT payment_id, order_id, amount, status, payment_method,
  processed_at, settled_at
FROM payment_events
WHERE status IN ('completed', 'refunded', 'failed');
-- Other teams query via PostgreSQL: SELECT * FROM payments_data_product WHERE ...

Each team defines, maintains, and serves their data product as a streaming materialized view.

Data Mesh + Streaming Architecture

Domain A (Orders)     → RisingWave → orders_data_product MV
Domain B (Payments)   → RisingWave → payments_data_product MV
Domain C (Shipping)   → RisingWave → shipping_data_product MV
                                          ↓
                                   Consumer teams query via PG
                                   (cross-domain joins if needed)

Frequently Asked Questions

How does streaming data mesh differ from batch data mesh?

Batch data mesh publishes data products as tables refreshed on schedule. Streaming data mesh publishes materialized views that update in real time. The interface is the same (SQL query), but the freshness is seconds instead of hours.