Datacoral No-Code Data Integration
Redshift Integration

Datacoral: Database replication using Change Data Capture

No-code data replication with data quality guarantees


Organizations today deeply understand the need for comprehensive data analytics. Data continues to be siloed in many different data sources (databases, APIs, file systems) and the volume and velocity of data continue to grow rapidly. The solution that data teams are searching for is a fast, scalable cloud warehouse combined with an easy-to-use data engineering solution that helps them reliably centralize data from data sources such as databases.
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The Challenge

Centralizing an organization’s data from different data sources — especially databases — into a warehouse is a frustrating experience. It involves piecing together multiple complex systems while dealing with increasing variety, velocity, and volumes of data. Change Data Capture (CDC) is the recommended way to replicate data from large databases, but companies need to think about the unique challenges posed by CDC, like replication lag, data quality, historical syncs, and schema changes.


Amazon Redshift combined with an AWS-native, data pipeline solution like Datacoral is the modern answer to today’s analytics challenges.
  • End-to-end pipelines – Easy to deploy fully-managed integrations with data and schema reliably replicated into Amazon Redshift.
  • Source system support – Multiple types of sources (databases, APIs, etc.) and complex CDC sources should work out-of-the-box.
  • Complete observability – Data quality, monitoring, and alerting are critical parts of ETL — not an afterthought.


No-code CDC Connectors

Get data flowing from databases such as PostgreSQL, MySQL, MongoDB into Amazon Redshift with just a few clicks.

Real-time Data Replication

Datacoral reads from database logs and writes to Amazon Redshift with minimal replication lag so data teams always have complete and up-to-date data.

Data Quality Checks

Out-of-the-box monitoring sends out alerts on failures. Regular, automated data quality checks make sure that data matches between source and destination at all times.

Schema Change Handling

As tables and columns are added, removed, or modified in your source database, Datacoral ensures that your tables in Amazon Redshift remain in sync.

Fast Historical Syncs

Datacoral is deployed in your AWS VPC, which means that no data leaves your system. Data is encrypted at rest and in transit and all actions are audited.

Data Security

Datacoral is deployed in your cloud VPC which means that no data leaves your system. Data is encrypted at rest and in transit and all actions are audited.

Amazon RedShift Architecture

How it Works:

  1. Automated schema mapping from source DB to Amazon Redshift
  2. Automated historical syncs read from the replica database
  3. Change logs read from database and applied to Amazon Redshift tables
  4. Automated data quality checks run regularly, comparing source to destination
  5. Schema changes are detected as they happen and applied to Amazon Redshift


Dr Chrono

“Datacoral’s CDC connector reliably replicates data from MySQL to Amazon Redshift while minimizing the load on the database and warehouse. Being fully deployed in our AWS VPC, its architecture was a big selling point and Datacoral has become our CDC partner who we can fully trust with our data.

We are now able to make better decisions because the data has allowed us to gain a deeper understanding of our customers and their needs.”

– Jerry Yi, Director of Data at DrChrono

Want to learn more about Change Data Capture (CDC)?

Ready to move your MySQL or PostgreSQL data? Try Datacoral now.

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