Stream into MySQL with your free account
Deliver data from databases, SaaS apps, APIs, files, and streaming systems into MySQL 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
MySQL connector details
The Estuary MySQL connector materializes data collections into MySQL tables for downstream analytics or application use. It supports standard and delta update modes, ensuring efficient incremental writes. The connector works with both self-hosted and managed MySQL services like Amazon RDS, Google Cloud SQL, and Azure Database for MySQL, with optional SSH tunneling for secure connectivity.
- Writes data collections to MySQL tables in real time
- Supports standard and delta updates for optimized performance
- Compatible with RDS, Cloud SQL, and Azure Database for MySQL
- Handles date-time normalization and time zone alignment automatically
- Enables secure connections via SSL or SSH tunneling
How to connect your data source to MySQL 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 MySQL
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 MySQL with tutorials and walkthroughs from our YouTube channel.
![Stream Data into Apache Iceberg Without Kafka #shorts video thumbnail]()
Stream Data into Apache Iceberg Without Kafka #shorts
You can stream database changes into Apache Iceberg without managing Kafka by using change data capture (CDC). This Short shows how it works with Estuary as an example: connect PostgreSQL or MySQL, capture inserts, updates and deletes from the database’s change log into durable Estuary collections, then deliver them to Iceberg tables with Estuary’s Apache Iceberg connector, which runs Spark jobs on AWS EMR Serverless. Historical backfills run alongside ongoing CDC, so updates aren’t missed during the initial load.
![What Is Change Data Capture (CDC)? Explained in 60 Seconds #dataengineering #changedatacapture video thumbnail]()
What Is Change Data Capture (CDC)? Explained in 60 Seconds #dataengineering #changedatacapture
Change data capture (CDC) tracks every insert, update, and delete in a database and sends only those changes downstream. Log-based CDC reads the database’s transaction log, like the Postgres WAL or MySQL binlog, so it catches deletes and runs in near real time.
![How to Replicate MySQL to Snowflake with CDC (Step-by-Step) #dataengineering video thumbnail]()
How to Replicate MySQL to Snowflake with CDC (Step-by-Step) #dataengineering
Replicate MySQL to Snowflake with change data capture (CDC). Estuary reads every insert, update, and delete from the MySQL binary log and merges them into Snowflake on your sync schedule.
![Introducing Estuary Agent Skills: Build Data Pipelines with AI video thumbnail]()
Introducing Estuary Agent Skills: Build Data Pipelines with AI
Estuary Agent Skills give your AI coding assistant the Estuary-specific context it needs to build and operate real-time data pipelines. Ask in plain English, capture my Postgres database into Snowflake, load these collections into BigQuery, or why is this connector failing, and your assistant knows the workflow.
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 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 MySQL, 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 MySQL through Estuary.
- Transform and route data through Estuary collections before delivering it to MySQL.
See what you can connect to MySQL:
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
| Estuary | Batch ELT/ETL | DIY Python | Kafka | |
|---|---|---|---|---|
| Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
| Latency | <100ms to scheduled | 5min+ | Varies | <100ms |
| Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
| Scale | ||||
| Maintenance Effort | Low | Medium | High | High |
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