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    REAL-TIME ETL & CDC

    Stream into Databricks 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
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    01. Select a source02. Transform in-flight03. Deliver to Databricks
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    Databricks logo

    Databricks connector details

    Estuary’s Databricks connector materializes Flow collections into tables in a Databricks SQL Warehouse. Data changes are first written to a Unity Catalog Volume and then applied transactionally to Databricks tables, ensuring reliable delivery of real-time updates. This connector supports both standard merges and delta updates for high-performance CDC workflows.

    • Real-time CDC data sync from Flow collections into Databricks tables
    • Choice of standard (merge) or delta updates to optimize performance and costs
    • Native integration with Databricks Unity Catalog for secure, managed storage
    • Flexible sync scheduling to balance freshness and warehouse costs

    For more details about the Databricks connector, check out the documentation page.

    How to connect your data source to Databricks 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 Databricks

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

    Learn more with some related videos

    Dive deeper into Databricks with tutorials and walkthroughs from our YouTube channel.

    Get Started Free

    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
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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 Databricks 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 Databricks insights always reflect the latest data by connecting your databases to Databricks with change data capture.
    • Or connect critical SaaS apps to Databricks with real-time data pipelines.

    See how you can integrate any source with Databricks:

    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.