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Challenge

Legacy Data Storage Schema Migration Bridge Engine

GovTech's data transformation initiatives demand modernizing legacy storage structures into cloud-native formats. Construct an automated data schema migration bridge that extracts legacy database structures, resolves schema drift, and generates zero-downtime SQL migration scripts.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Build an automated legacy storage schema translation and drift detection pipeline.

Delivery guide

How work is evaluated

Evaluation

Evaluates accuracy of SQL migration script generation and schema compatibility.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

valid_sql_syntax

Ensures valid modern SQL output

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

type_conversion_accuracy

Accuracy of legacy to modern type mapping • target: 1 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Parse legacy relational schema representations

  • Automatically map obsolete field types to cloud-native database standards

  • Generate validated zero-downtime DDL migration scripts

Resources and assets

Reference links and supporting material

Dataset notes

Synthetic legacy database schemas from public sector system archives.

Challenge setup

Evaluates accuracy of SQL migration script generation and schema compatibility.

Challenge input

Legacy SQL DDL string

sqlglot

Automated multi-dialect SQL conversion

Evaluated output

JSON containing modern_sql_ddl and field_mapping_summary

Evaluation checks
  • Ensures valid modern SQL output
  • Accuracy of legacy to modern type mapping • target: 1 • range: 0-1
Configured evaluation evidence
  • Benchmark: SQLTrans-Bench
  • Type Conversion Accuracy target: 1
  • 1 public reference case
Configured runtime
  • Python execution harness
  • Python sandbox (unavailable on Versalist)

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • MemGPT · Required
  • deepchecks · Optional
  • SonarSource · Optional

Evaluation contract

  • valid_sql_syntax · Weight 1
  • type_conversion_accuracy · Weight 1

Metrics

  • type_conversion_accuracy · Target 1

Benchmarks

  • SQLTrans-Bench
  • general

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: Legacy SQL DDL string

    Output: JSON containing modern_sql_ddl and field_mapping_summary

    Execution harness: Python

Evaluation tools

  • sqlglot · SQL Parser & Transpiler

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Legacy Data Storage Schema Migration Bridge Engine