Watch step-by-step video tutorials that walk you through every aspect of SQL Tran. Topics include software installation, migration setup, data partitioning strategies, handling schema changes, and more advanced functionality.
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Running an agent on a different machine is no more complex than copying binaries to the new machine and running a single executable file.
SQL Tran is a tool designed to streamline the workflow of database management by providing a user-friendly interface for database translation and assessment.
Users can begin by selecting their source database type, such as Synapse Dedicated Pool, and then upload their database scripts in various formats, including SQL, zip, or deckpack files.
The tool offers a quick and efficient static analysis and assessment of the database, with translation of objects available for assessment purposes for free, while full translation may require a subscription.
Consultants and users can review the translation, seek approval, and effortlessly unlock instant translation for comprehensive database management.
The project assessment in SQL Tran is efficiently integrated within the translation process, providing a seamless approach to converting SQL Server databases, like AdventureWorks 2017, to other formats while highlighting potential incompatibilities.
Users can evaluate translation accuracy by comparing source and target codes, with SQLTrain offering a few free translations to demonstrate its capabilities.
The tool uses an abstract syntax tree to assess the complexity of database objects, determining pricing based on the complexity rather than just the lines of code.
Once satisfied with the assessment, users can proceed with full translations at a cost, gaining access to all functionalities and object translations through a simple unlocking step.
The SQL Tran interface provides various features to enhance database management and navigation.
The workspace section, a crucial part of the interface, facilitates user interaction with database objects and identifies translation issues or problems, which may require manual intervention if no automatic solution is available.
For efficient navigation, especially in large databases, the interface supports keyboard shortcuts and fuzzy search capabilities to quickly locate and manage database objects.
Additionally, the tool offers features like a report screen for tracking errors and dependencies, a test generation option to ensure business logic remains intact, and a scratch pad function for real-time code translation and testing.
The "Bring Your Own License" plan of SQL Tran allows users to fine-tune code translation on both the source and target.
A specific problem is highlighted with a table using a CLR function, "get level," which has no equivalent in fabric warehouse, leading to translation issues.
The solution involves overriding the source to adjust or eliminate unnecessary elements, ensuring translations are cleaned and fixed for the next issue.
Users can also choose to ignore certain objects if analyzing the code indicates they won't be used, although this may invalidate related objects.
The SQL Tran system utilizes a highly efficient Hummingbird parsing engine capable of parsing millions of lines of SQL code per second, enabling near real-time code translation.
This feature is integrated into SQL Tran's Scratch Pad accessible exclusively through the Bring Your Own License plan.
Users can instantly see code translations, allowing for dynamic error checking and real-time data type transformations during development.
This capability is particularly beneficial for prototyping changes quickly and efficiently.
A core engine that examines your entire SQL codebase without executing it, tracking object references and building full dependency and data-lineage maps across all database objects.
It highlights unresolved references and broken dependencies directly in the editor and lets you navigate to definitions, helping you quickly understand and fix issues in complex SQL projects.
This analysis underpins other advanced capabilities like automatic test generation and reliable translation by ensuring the tool understands how objects relate.
Finally, it enables instant feedback (e.g., underlining invalid references) while editing or exploring code, improving code quality and maintainability.
The exporting and importing projects feature lets you save a SQL Tran project to a file and then bring it into another SQL Tran instance, enabling you to move work between environments or versions of the tool.
Because SQL Tran runs in your own Azure tenant and Spectral Core cannot access your data, exports provide a secure way to preserve and transfer projects when upgrading to a newer instance.
You typically export the project from your current instance, deploy a new SQL Tran instance, then import the project file into the new environment.
This process ensures that your database migration definitions, translated code, and related metadata are consistently carried over without relying on external access.
The data lineage feature in SQL Tran uses the built-in static analysis engine to automatically map and display all dependencies for a selected database object, showing both what it depends on and what depends on it.
This lineage information is instantly available in the Workspace side-panel under the Analysis tab and helps with impact analysis by highlighting broken references when object names change or are missing.
Because it’s maintained continuously as the project changes, users get up-to-date visibility into object relationships across the entire codebase without running queries.
This deep insight into dependencies supports better navigation, understanding of complex codebases, and more reliable translation and testing workflows.
How to set up and run the testing phase of your migration project by configuring staging database connections and generating tests for database objects.
It describes how SQL Tran can automatically generate appropriate tests for tables, views, procedures, and functions based on how they’re used, including how parameters influence test data selection for procedural objects.
The page clarifies that staging connections should point to non-production databases so that tests can exercise real queries and data comparisons without risk to live systems.
It’s part of the broader Tests section that guides users through validating that translated SQL behaves correctly by comparing source and target results.
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