Stream into Alloy DB for Postgres with your free account
Continously ingest and deliver both streaming and batch change data from 100s of sources using Estuary's custom no-code connectors.
- <100ms Data pipelines
- 100+ Connectors
- 2-5x less than batch ELT
Alloy DB for Postgres connector details
The AlloyDB materialization connector continuously writes data from Estuary Flow collections into AlloyDB tables, allowing you to keep a fully managed, PostgreSQL-compatible database in Google Cloud up to date with your real-time data streams.
- PostgreSQL-compatible: Built on Estuary’s PostgreSQL connector, providing identical configuration and behavior
- Secure connectivity: Uses SSH tunneling to connect to AlloyDB instances (since IP allowlisting isn’t supported)
- Automatic table creation: Flow creates and manages target tables automatically based on your collection schemas
- Delta or merge updates: Supports both incremental (delta) and standard merge-based updates
- Ideal for analytics and applications: Perfect for workloads that need transactional consistency and scalable cloud performance
💡 Tip: Configure your SSH bastion VM within the same Google Cloud project as your AlloyDB instance for secure, low-latency connections.
HIGH THROUGHPUT
Distributed event-driven architecture enable boundless scaling with exactly-once semantics.
DURABLE REPLICATION
Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.
REAL-TIME INGESTION
Capture and relay every insert, update, and delete in milliseconds.
Real-timehigh throughput
Point a connector and replicate changes to Alloy DB for Postgres in <100ms. Leverage high-availability, high-throughput Change Data Capture.Or choose from 100s of batch and real-time connectors to move and transform data using ELT and ETL.
- Ensure your Alloy DB for Postgres insights always reflect the latest data by connecting your databases to Alloy DB for Postgres with change data capture.
- Or connect critical SaaS apps to Alloy DB for Postgres with real-time data pipelines.
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Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
| Estuary | Batch ELT/ETL | DIY Python | KAFKA | |
|---|---|---|---|---|
| Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
| Speed | <100ms | 5min+ | Varies | <100ms |
| Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
| Scale |
Deliver real-time and batch data from DBs, SaaS, APIs, and more
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