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    Stream into Amazon Aurora for Postgres with your free account

    Deliver data from databases, SaaS apps, APIs, files, and streaming systems into Amazon Aurora for Postgres using Estuary's pre-built connectors. Run pipelines from real-time streaming to scheduled batch based on connector capabilities.

    • <100ms to batch
    • 200+ connectors
    • Managed data pipelines
    Try it freeWatch Demo
    01. Select a source02. Transform in-flight03. Deliver to Amazon Aurora for Postgres
    Amazon Aurora for Postgres logo
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    Amazon Aurora for Postgres logo

    Amazon Aurora for Postgres connector details

    The Amazon Aurora for PostgreSQL materialization connector in Estuary delivers data from Estuary collections into tables in an Aurora PostgreSQL-compatible database. It supports continuous materialization from real-time or batch pipelines and uses standard merge-based updates by default to keep destination tables synchronized.

    • Materializes Estuary collections directly into Amazon Aurora for PostgreSQL tables
    • Standard merge-based updates by default to keep existing rows synchronized
    • Optional delta updates for workloads where changes should be applied incrementally
    • Optional hard deletes so records deleted at the source can also be deleted from the destination
    • Automatic table creation for tables managed by the connector
    • AWS IAM or username/password authentication
    • Direct connectivity or SSH tunneling for secure access to Aurora instances
    • Configurable SSL modes for encrypted database connections
    • Custom SQL during table creation for indexes or other table-level configuration
    • Configurable destination schemas and table names for individual bindings

    Estuary creates and manages the destination tables used by the materialization. You can configure a default PostgreSQL schema, override it for individual bindings, and optionally run additional SQL when a table is created—for example, to create indexes automatically.

    For more details about the Amazon Aurora for Postgres connector, check out the documentation page.

    How to connect your data source to Amazon Aurora for Postgres in 3 easy steps

    1. 1

      Connect your data source

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

    2. 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. 3

      Sync to Amazon Aurora 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.

    4.8/5

    HIGH THROUGHPUT

    Distributed, event-driven architecture scales for demanding data workloads.

    DURABLE COLLECTIONS

    Store data as it moves so you can transform, replay, and deliver it downstream.

    FLEXIBLE LATENCY

    From <100ms CDC and real-time streaming to scheduled batch, depending on connector capabilities.

    From <100ms to batch

    Estuary supports CDC, real-time streaming, incremental syncs, and scheduled batch across its connector ecosystem. Bring data from databases, SaaS apps, APIs, files, and event streams into Amazon Aurora for Postgres, with capture and delivery cadence based on connector capabilities and pipeline configuration.

    • Connect data from operational databases, SaaS applications, APIs, files, and streaming systems to Amazon Aurora for Postgres through Estuary.
    • Transform and route data through Estuary collections before delivering it to Amazon Aurora for Postgres.

    See what you can connect to Amazon Aurora for Postgres:

    Details

    or choose from these popular data sources:

    PostgreSQL logo
    PostgreSQL
    MySQL logo
    MySQL
    SQL Server via CDC logo
    SQL Server via CDC
    MongoDB logo
    MongoDB
    Apache Kafka logo
    Apache Kafka
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    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$$$-$$$$$-$$$$$-$$$$
    Latency<100ms to scheduled5min+Varies<100ms
    EaseAnalysts can manageAnalysts can manageData EngineerSenior Data Engineer
    Scale
    Maintenance EffortLowMediumHighHigh

    One platform for real-time and batch data pipelines

    Detailed Comparison

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

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    Connection-1

    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.