Estuary

Stream into MariaDB with your free account

Deliver data from databases, SaaS apps, APIs, files, and streaming systems into MariaDB 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
01. Select a source02. Transform in-flight03. Deliver to MariaDB
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MariaDB connector details

The MariaDB materialization connector in Estuary delivers data from your pipelines directly into your destination system — continuously and in real time. Using merge-based writes, Estuary efficiently updates only changed records, ensuring your destination stays perfectly in sync without unnecessary reprocessing. Whether for analytics, AI, or operational use cases, Estuary provides a reliable, cost-efficient way to keep MariaDB up to date.
  • Log-based CDC for high-performance, low-impact data capture
  • Automatic schema evolution to handle changes in source structure without manual intervention
  • Unified streaming and batch ingestion in the same pipeline
  • Hybrid deployment and BYOC support for security and control
  • Fault-tolerant pipelines that resume automatically from the last checkpoint
  • Kafka API connectivity for direct integration into streaming ecosystems

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

How to connect your data source to MariaDB 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 MariaDB

    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.

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 MariaDB, 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 MariaDB through Estuary.
  • Transform and route data through Estuary collections before delivering it to MariaDB.

See what you can connect to MariaDB:

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
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$$$-$$$$$-$$$$$-$$$$
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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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.