How Software Automatically Translates Database Queries for Different Storage Systems

A system that intercepts database queries written for traditional relational databases and automatically translates them to work with non-relational databases, allowing developers to switch storage systems without rewriting their application code.

What it covers

This patent describes a middleware layer that sits between an application and its database. When the application sends a query in a language like SQL, the system intercepts it, parses it into a structural tree, and translates it into a different query language supported by a non-relational database. After executing the new query, the system monitors the application to see if it crashes or reports errors, effectively testing if the new database can successfully replace the old one. This allows engineers to migrate data from rigid relational tables to more flexible formats without manually updating every line of their application's code.

What it doesn't cover

• —Does not cover manual database migration scripts or manual code refactoring.
• —Does not cover query translation that happens at compile-time rather than during runtime execution.
• —Does not cover systems that do not perform error monitoring or failure detection after the translation occurs.

The clever bit

The system doesn't just translate the query; it treats the translation as a live experiment by monitoring the application's response to the new database output to ensure it doesn't trigger errors or exceptions.

Why it matters

As companies scale, they often outgrow traditional relational databases (like MySQL) and move to NoSQL or key-value stores for better performance. Rewriting legacy code to support new database languages is expensive and risky. This patent provides a way to automate that transition, reducing the downtime and human error associated with massive infrastructure migrations.

Real-world examples

• 1.Cloud database migration tools
• 2.Database abstraction layers
• 3.Legacy application modernization platforms