Scaling biology in the
service of humanity

About the company

GreenLight Bio were founded to create solutions that reach the whole world, not just its richest parts. Our proven, stable, and flexible platform means it can be deployed cost-effectively to tackle problems from pandemics to crop pests.

SqlDBM helped:
  • Automate a cloud migration from SQL Server to Snowflake
  • Establish a modeling framework from design to transformation
  • Provide visibility in the data landscape from relational models to logical pipelines and views
There was no before scenario. Ours is a new development–we did our due diligence and went with SqlDBM. Karthikeyan Shanthakumar - Senior
Datawarehouse Architect

Automate lift-and-shift migration

Database migrations, even the direct lift-and-shift variety, are still formidable ordeals. When GreenLight Bioscience decided to modernize its data landscape by migrating to the Snowflake Data Cloud, its first step was to look for a modeling tool–something intuitive, web-based, and maintenance-free but with the rich technical prowess to support a migration project and future enhancements to the model. SqlDBM ticked all those boxes by offering native support for GreenLight’s SQL Server source system and their Snowflake target and allowing automated DDL conversion between the two.

SqlDBM’s project conversion feature saved GreenLight’s engineers weeks of labor by automatically converting their existing SQL Server model into Snowflake and achieving a 99% conversion success rate (some adjustments to convert semistructured data into Snowflake VARIANT). Not only did SqlDBM accelerate the migration to and deployment of the new data model to Snowflake, it gave GreenLight an all-in-one resource to scale the design in the future through an integrated data dictionary, DevOps workflow, and version control.

Establish a new development


Following a successful migration, GreenLight’s data team continues to rely on SqlDBM to evolve the data model and leverage Snowflake’s cloud-native architecture to add value to the business. Through a visual design interface, which requires no coding and checks models for semantic and structural integrity before deployment, the data team ensures accurate and consistent designs are generated every time. Automating repeatable and time-consuming tasks keeps the team lean and focused on high-value work.

The models generated in SqlDBM are instantly sharable to the entire team and visible in real-time by the engineers engaged in creating the logic to move data across them. SqlDBM doesn’t stop at relational links; it allows the team to document data pipelines through virtual relationships on the same diagram as physical objects and include logical Snowflake objects like stored procedures and views.

Maintain visibility and data


With Snowflake’s scalable architecture and a growing data landscape, GreenLight’s Data team can keep tabs on all their data assets and coordinate them using SqlDBM. Analysts and business users can now use the same models used to migrate and expand the business data model to find new data assets and relate them to existing datasets. In a few simple steps, a cloud-native tool like SqlDBM integrates with the other tools in GreenLight’s data stack, such as git repositories, Confluence, and Jira–keeping the entire team coordinated and informed.