Today, we are excited to announce the availability of Delta Live Tables (DLT) on Google Cloud. With this launch, enterprises can now use DLT to easily build and deploy SQL and Python pipelines and run ETL workloads directly on their lakehouse on Google Cloud.
In order to power analytics, data science and machine learning, data engineers need to turn raw data into fresh, high-quality, structured data. DLT provides Databricks customers a first-class experience that simplifies this data transformation on Delta Lake on top of Google Cloud Storage. DLT helps teams do ETL development and management with declarative pipeline building, improved data reliability and cloud-scale production operations that help build the lakehouse foundation.
This launch further strengthens the partnership between Databricks and Google Cloud, bringing together the powerful Databricks Lakehouse capabilities customers love with the data analytics solutions and global scale available from Google Cloud.
What Delta Live Tables brings to Google Cloud:
- Easy pipeline development and management – use declarative tools to build and manage data pipelines – in both batch and streaming.
- Built-in data quality – prevent bad data from flowing into pipelines and avoid and address data quality errors with predefined policies and data quality monitoring.
- Simplified operations – Gain deep visibility into pipeline operations with tools to visually track operational stats and data lineage and automatic error handling.
Delta Live Tables is currently in Gated Public Preview for Databricks on Google Cloud. Customers can request access to start developing DLT pipelines here. Visit our Demo Hub to see a demo of DLT or read the DLT documentation to learn more.
As this is a gated preview, we will onboard customers on a case-by-case basis to guarantee a smooth preview process. We have limited slots for preview and hope to include as many customers as possible. If we are unable to onboard you during the gated preview, we will reach out and update you when we are ready to roll out broadly.