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REAL-TIME ETL & CDC

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
01. Select a source02. Transform in-flight03. Deliver to Alloy DB for Postgres
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Alloy DB for Postgres logo

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.

For more details about the Alloy DB for Postgres connector, check out the documentation page.

How to connect your data source to Alloy DB for Postgres in 3 easy steps

1

Connect your data source

Select from more than 100 supported databases and SaaS platforms including PostgreSQL, MySQL, SQL Server, MongoDB, and Kafka.

2

Prepare and transform your data

Apply transformations and schema mapping as data moves whether you are streaming in real time or loading in batches.

3

Sync to Alloy DB for Postgres

Continuously or periodically deliver data into your destination with support for change data capture and reliable delivery for accurate insights.

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Trusted by data teams worldwide

All data connections are fully encrypted in transit and at rest. Estuary also supports private cloud and BYOC deployments for maximum security and compliance.

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HIGH THROUGHPUT

Distributed event-driven architecture enable boundless scaling with exactly-once semantics.

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DURABLE REPLICATION

Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.

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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.

See how you can integrate any source with Alloy DB for Postgres:

Details

or choose from these popular data sources:

PostgreSQL logo
PostgreSQL
MySQL logo
MySQL
SQL Server logo
SQL Server
MongoDB logo
MongoDB
Apache Kafka logo
Apache Kafka
BigQuery logo
BigQuery
Snowflake Data Cloud logo
Snowflake Data Cloud

Don't see a connector?Request and our team will get back to you in 24 hours

Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.

Feature Comparison

EstuaryBatch ELT/ETLDIY PythonKafka
Price$$$-$$$$$-$$$$$-$$$$
Speed<100ms5min+Varies<100ms
EaseAnalysts can manageAnalysts can manageData EngineerSenior Data Engineer
Scale
Maintenance EffortLowMediumHighHigh
Detailed Comparison

Deliver real-time and batch data from DBs, SaaS, APIs, and more

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Popular sources/destinations you can sync your data with

Choose from more than 100 supported databases and SaaS applications. Click any source/destination below to open the integration guide and learn how to sync your data in real time or batches.