SQL Server to Snowflake Migration Assessment Tool

Why migration assessments reduce delivery risk

SQL Server to Snowflake migrations are frequently underestimated. Procedural logic, database dependency patterns relevant to ETL modernization, unsupported SQL patterns, and cross-system references are typically not visible in a table count or schema summary — and surface late in the program when correction is expensive.

A structured migration complexity assessment surfaces these drivers early, while planning and budgets are still adjustable.

Identify complexity early — detect procedural and dependency risks relevant to migration and ETL modernization before project kickoff
Improve estimation and planning — use analyzed complexity signals, inventory, and dependencies instead of assumptions
Prioritize remediation focus — focus on objects with the highest rewrite and validation impact

What SQL2Snow analyzes

SQL2Snow scans SQL Server environments to produce a structured picture of migration complexity. Analysis is deterministic and rule-based — results are explainable and repeatable.

Inventory

Database inventory analysis

Tables, views, stored procedures, functions, triggers, and indexes — scanned across one or more databases to produce a structured object inventory.

Procedural logic

Stored procedure analysis

Identifies patterns that drive rewrite effort and testing scope. Detected signals include: CURSOR #temp tables dynamic SQL TRY/CATCH RAISERROR

Compatibility

Unsupported SQL pattern detection

Flags SQL Server constructs with no direct Snowflake equivalent that require manual redesign: CLR XML patterns OPENQUERY linked servers cross-db references

Complexity scoring

Migration complexity indicators

Each object is scored for complexity (Low / Medium / High) using deterministic rule hits, producing a ranked list of highest-complexity migration targets.

Dependencies

Dependency patterns relevant to ETL modernization

Surfaces cross-database references, linked servers, and external dependency patterns that can increase coordination and redesign effort during migration.

Assessment outputs

SQL2Snow generates structured, human-readable outputs designed for both technical review and executive planning discussions.

Technical outputs

Object inventory: tables, views, procedures, functions
Complexity scores per object (Low / Medium / High)
Rule-hit detail: cursors, temp tables, dynamic SQL, cross-db references
Top highest-complexity objects for remediation focus
Draft Snowflake DDL for table schemas
Structured assessment JSON export

Planning and executive outputs

Migration Complexity Score (0–100)
Estimated effort and Low–High range
Complexity breakdown by object and level
Top complexity drivers and highest-complexity objects
Prioritized recommendations
Executive-ready migration assessment summary

Common SQL Server to Snowflake migration complexity drivers

Migration complexity is commonly driven by stored procedure rewrites, dependency density, testing, data model refactoring, ETL and pipeline gaps, and organizational coordination.

Stored procedure rewrite Dependency density Testing amplification Data model refactoring ETL & pipeline gaps Organizational coordination

Explore Migration Cost & Complexity Drivers →

Assessment workflow

SQL2Snow runs locally against your SQL Server environment. No data export required.

Connect Point SQL2Snow at your SQL Server instance. Scans run locally — no data leaves your environment.

Analyze SQL2Snow scans objects for complexity signals, unsupported patterns, and dependency relationships.

Review Receive an HTML assessment report, structured assessment JSON, and draft Snowflake DDL to support planning decisions.

Assess your SQL Server environment

Run SQL2Snow locally to generate your migration assessment.

Download SQL2Snow View Sample Report