SQL Query Builders & Database Migration Tools
Generate production-ready SQL Server PIVOT and UNPIVOT queries, plus migrate databases between SQLite, Access, and SQL Server. Each tool handles the heavy lifting automatically — syntax, type mapping, relationship handling — so you can focus on the logic, not the boilerplate.
Static PIVOT vs Dynamic PIVOT — Which Do You Need?
| Static PIVOT | Dynamic PIVOT | |
|---|---|---|
| Column values | Hardcoded in query | Discovered at runtime |
| Handles new values | No — requires code change | Yes — automatic |
| Performance | Slightly faster | Slightly slower (builds SQL string) |
| Readability | Clearer, easier to audit | Harder to read |
| When to use | Known, fixed set of values (months, quarters) | Unknown or changing values (product names, regions) |
| Risk | None | SQL injection risk if source is user input |
When to Use UNPIVOT
UNPIVOT is the reverse of PIVOT: it takes columns and turns them into rows. This is useful when you have a wide table where repeated column groups should be normalized.
Example: a sales table with Jan_Sales, Feb_Sales, Mar_Sales columns. UNPIVOT turns each of those columns into a row with a Month column and a Sales value column — proper normalized form.
- Normalizing denormalized reporting tables
- Preparing data for time-series analysis
- Feeding data into tools that expect long format
What This Tool Does
A collection of browser-based SQL query builders that generate complex SQL patterns — pivots, unpivots, date spines, deduplication queries, and data conversions — without requiring you to write the syntax from scratch.
Who This Is For
- Data analysts who know what query shape they need but don't want to write complex SQL boilerplate
- SQL developers generating pivot and unpivot queries that have dialect-specific syntax
- DBAs automating repetitive query generation tasks across multiple tables
- Anyone learning advanced SQL patterns through generated, correct examples
Example: Input: Describe your table structure: source table, row field, column field, and aggregate → Output: A complete, ready-to-run SQL query for your specified pattern and database dialect