Mapping MySQL Data Types to SQL Server

A data type name can look familiar and still hold a different range. Mapping MySQL data types to SQL Server starts with the values that actually exist, then checks how the application uses them. The table definition alone does not answer that question.

Inventory Values Before Mapping MySQL Data Types

Export the MySQL schema and profile the source columns before choosing targets. Record null counts, minimum and maximum numeric values, longest text, and exceptional dates using queries on the source. Keep those measurements tied to a consistent source snapshot. A type declaration says what is permitted, while the data tells you what the migration must preserve.

I ask for the application rules too. A column storing flags as tiny integers can be treated as Boolean in one service and as a numeric status in another. Which interpretation must survive? Review code paths that cast, compare, or sort the column. The target type is part of an application contract, not only a storage decision.

Use a Mapping Table With Traps

This compact table is a starting point for review, not a universal conversion rule. Choose the target only after checking source ranges, signedness, character set, and application behavior. A source value that fits today can still be allowed to grow by the source schema. Decide whether the target preserves the allowed range or only a deliberately narrowed business range.

I keep an explicit exception list beside the table. Automated migration tools are useful for initial mappings, but their output needs tests at the edges. The trap column is the part I read first. Familiar type names have a talent for hiding their least familiar values.

Handle Signed and Unsigned Integers

SQL Server tinyint covers nonnegative values, while MySQL TINYINT can be signed or unsigned. A signed source TINYINT needs a target that holds negative values, such as smallint. MySQL INT UNSIGNED extends beyond the maximum signed SQL Server int, so bigint is a safer direct target. MySQL BIGINT UNSIGNED can exceed SQL Server bigint. A suitable decimal type or a redesigned key representation needs review.

The T-SQL sample shows target declarations for boundary-sized example values without claiming those values exist in your source. Run source-side profiling before choosing a narrower type. I test the largest observed value and the largest source-permitted value when future writes matter.

SELECT
    CAST(4294967295 AS bigint) AS UnsignedIntExample,
    CAST(18446744073709551615 AS decimal(20,0)) AS UnsignedBigIntExample;

Choose Text Types for Meaning When Mapping MySQL Data Types

Map MySQL text and varchar columns according to encoding, length, collation, and use. SQL Server varchar stores character data according to its collation and encoding rules, while nvarchar stores Unicode data. The target length must be tested against characters and bytes, not inferred from a column name. Large text belongs in a max type only when the application truly needs it.

I check unique indexes and search behavior after the text mapping. A changed collation can merge keys that were distinct in the source. A changed length can truncate or reject data. Run a sample with accented text, emoji, trailing spaces, and the longest source value. The receiving system, not the export file name, decides whether the characters survived.

Treat DATETIME as a Range Decision

MySQL DATETIME accepts dates before the earliest SQL Server datetime value. SQL Server datetime2 has a wider date range and better precision choices, so it is usually the target to evaluate first for ordinary timestamps. Check actual source values, fractional seconds, and zero-date practices. A zero date needs a business mapping because SQL Server date types do not represent it.

The query below illustrates a conversion check. TRY_CONVERT returns NULL when the sample cannot become datetime. Use a staging table with original text for real migration exceptions so you can distinguish an invalid source value from an original NULL. I never replace exceptional historical dates with the current date to make a load green.

SELECT
    TRY_CONVERT(datetime, '1000-01-01') AS AsDatetime,
    TRY_CONVERT(datetime2, '1000-01-01') AS AsDatetime2;

Review Time Zone Behavior

MySQL TIMESTAMP and DATETIME have different time zone behavior. SQL Server datetime2 does not carry an offset. Datetimeoffset does. Decide whether the stored value represents a local wall clock, a UTC instant, or an offset-bearing event. Keep that decision visible in the target schema and application API. A migration can preserve every digit while changing the moment the value represents.

I test one record around a daylight saving transition where the application uses local time. That is a functional test, not a claim about your data. If the source stores UTC, verify the export and import do not apply an extra conversion. Record the intended display zone separately from the stored instant.

Check Defaults, Identity and Constraints

When mapping MySQL data types, check how they interact with defaults and constraints. MySQL AUTO_INCREMENT needs an identity or sequence strategy. Boolean-like tinyint columns need an agreed target range and check constraint if only two states are valid. Numeric decimal precision and scale must preserve money or measurement rules. Compare default expressions rather than copying their text literally.

SSMA can produce an initial schema conversion and highlight unsupported patterns. Review generated types with the mapping table and source profile. I focus on columns used in joins, keys, and application filters first, because a mismatch there causes broader failures than a display-only field. Build a small load that exercises those columns before the full transfer.

Validate Mapping MySQL Data Types at the Destination

After loading, compare row coverage and targeted aggregates under the same source cutoff. Inspect minimum and maximum values for mapped numeric columns, failed date conversions, text lengths, and duplicate keys. Compare application behavior, especially sort order and equality, on both sides. A matching count does not prove correct mapping of MySQL data types.

Keep the source-to-target decision for every exception in a short record. If a value cannot be represented without changing meaning, stop and get the business rule resolved. The migration should make that conflict visible, not silently invent an answer. That is why the mapping table is a review tool rather than an automatic recipe.

Related reading on this blog: Puzzle: Datatime to DateTime2 Conversation in SQL Server 2017 and Datatype Decimal Explained: Datatype Numeric.

A type mapping is not a name substitution, it is a promise to preserve the values and behavior your app needs.

Published by Pinal Dave on SQLAuthority. More of my work at pinaldave.com.