Streaming Database

What Is a Streaming Database?

A streaming database ingests, processes, and serves data continuously in real-time. RisingWave is a PostgreSQL-compatible streaming database that uses SQL for continuous queries, materialized views, and sub-100ms latency — no Java required.

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SQL

PostgreSQL Compatible

Use psql, JDBC, or any PostgreSQL driver. Standard SQL for streaming queries and materialized views.

<100ms

End-to-End Latency

From event ingestion through processing to queryable results in under 100 milliseconds.

Exactly-Once

Semantics

Built-in state management with exactly-once guarantees. No manual checkpoints or RocksDB tuning.

50+

Connectors

Ingest from Kafka, Pulsar, Kinesis, PostgreSQL CDC, MySQL CDC, S3, and more out of the box.

How It Differs

What makes a streaming database different from a traditional database?

Traditional databases wait for queries. A streaming database pushes computation to the data, continuously updating results as new events arrive. Instead of polling stale tables, applications read always-fresh materialized views that reflect the latest state of your data streams.

Capability	Traditional DB	Streaming DB	RisingWave
Query Model	On-demand	Continuous	Continuous SQL
Data Freshness	Minutes to hours	Sub-second	Sub-100ms
State Management	Manual	Built-in	Automatic, exactly-once
Ingestion	Batch loads	Event streams	Kafka, CDC, S3, more
Result Serving	Query at read time	Pre-computed views	Queryable materialized views
SQL Support	Full SQL	Limited	Full PostgreSQL SQL

How It Works

How does RisingWave implement streaming database capabilities?

RisingWave combines a PostgreSQL-compatible SQL frontend with a distributed stream processing engine. You define sources, create materialized views with standard SQL, and query results instantly. State is managed automatically with exactly-once semantics and persistent storage.

PostgreSQL Wire Protocol

Connect with psql, JDBC, or any PostgreSQL client. Zero new tooling to learn.

Materialized Views as API

Define streaming logic as SQL materialized views. Results are always fresh and directly queryable.

Built-in Connectors

Ingest from Kafka, Pulsar, Kinesis, PostgreSQL CDC, MySQL CDC, S3, and more out of the box.

Automatic State Management

No RocksDB tuning or manual checkpoints. RisingWave handles state, recovery, and exactly-once semantics.

Use Cases

When should you use a streaming database instead of batch processing?

Use a streaming database when your business requires real-time decisions, live dashboards, or instant reactions to data changes. Batch processing works for historical reports, but any workload needing sub-second data freshness benefits from a streaming database approach.

→Real-time dashboards and operational monitoring that need second-level freshness
→Event-driven applications reacting to user behavior, transactions, or sensor data
→Feature engineering for ML models requiring up-to-the-second feature values
→CDC-based data synchronization keeping downstream systems in sync
→Alerting and anomaly detection triggering on live data patterns

Frequently Asked Questions

Is a streaming database the same as a message queue?

Can a streaming database replace my existing database?

What latency can I expect from RisingWave?

Does RisingWave support standard SQL?

Ready to try a streaming database?

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Incremental Materialized Views →Exactly-Once Streaming →