Datacoral No-Code Data Integration

Datacoral: Database replication using CDC

No-code data replication with data quality guarantees

CDC data integrations made easy

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 ETL solution that helps them reliably centralize data from data sources such as databases.

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 — replication lag, data quality, historical syncs, and schema changes.


Snowflake combined with a cloud-native, ETL solution like Datacoral is the modern answer to today’s analytics challenges.

Why Datacoral + Snowflake are the perfect pair:

  • End-to-end ETL Easy to deploy integrations managed over their lifecycle. Data and schema reliably replicated into Snowflake.
  • Source system support Multiple types of sources (databases, APIs, etc.) and complex CDC sources work out-of-the-box.
  • Complete observability Data quality, monitoring, and alerting are critical parts of ETL and not an afterthought.


No-Code CDC Connectors

Get data flowing from databases such as PostgreSQL and MySQL into Snowflake with just a few clicks.

Real-Time Data Replication

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

Schema Change Handling

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

Fast Historical Syncs

Historical syncs are performed by reading from replicas of your database. This leads to faster initial sync and reduces the load on your production DB.

Monitoring and 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.

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.

Datacoral easily moves your MySQL and PostgreSQL data into Snowflake

How it Works:

  1. Automated historical syncs read from the replica database
  2. Change logs read from database and applied to Snowflake tables
  3. Schema changes are detected as they happen and applied to Snowflake
  4. Automated data quality checks run on a regular basis


Flexport Modern Freight Forwarder

“We chose Datacoral’s Change Data Capture (CDC) connector to replicate our PostgreSQL databases to Snowflake after evaluating multiple SaaS and open-source solutions.

Datacoral’s fully managed pipeline reduces operational burden on our DevOps Team and our Security Team’s stringent requirements were satisfied with the entire product deployed on-prem in our cloud.”

– Stephan Goergen, Data Engineer at Flexport

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

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

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