MS SQL Alter Column Size: Why Your Database Might Scream At You

You're sitting there, coffee in hand, looking at a VARCHAR(50) that just isn't cutting it anymore. Some user with a hyphenated last name or a ridiculously long email address just broke your application's insert logic. It happens. So you think, "I'll just run a quick ALTER TABLE and call it a day."

Hold on.

Changing an ms sql alter column size seems like a trivial task—a one-liner, really—but if you’re working with a production database containing millions of rows, that one-liner is a landmine. You aren't just changing a definition in a metadata table. Depending on the data type and the version of SQL Server you're running, you might be triggering a massive, size-of-data operation that locks your table, eats your transaction log, and makes your users very, very angry.

The Basic Syntax (And Where It Trips You Up)

Let's get the boring stuff out of the way first. The standard way to handle an ms sql alter column size change is using the ALTER TABLE statement combined with ALTER COLUMN.

It looks like this:

ALTER TABLE YourTableName ALTER COLUMN YourColumnName VARCHAR(100);

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Simple? Kind of. But here’s the kicker: you have to restate the entire column definition. If that column was originally NOT NULL, and you forget to include NOT NULL in your ALTER statement, SQL Server will kindly (read: annoyingly) change it to NULL for you. I've seen senior devs accidentally introduce nullability into legacy systems because they were rushing. It's a mess to clean up.

Honestly, the syntax is the easy part. The hard part is understanding what happens under the hood when that command hits the execution engine.

Metadata Changes vs. Size-of-Data Operations

Not all alters are created equal. In older versions of SQL Server, almost any change to a column width was a "size-of-data" operation. This means SQL Server would create a new version of the table, copy every single row, and then drop the old one. If you had a 500GB table, you needed 500GB of free space just to change a VARCHAR length.

Things got better with SQL Server 2012 and 2016. Generally, increasing the size of a VARCHAR or VARBINARY column is now a metadata-only change. The engine just updates the sys-tables and says, "Cool, you have more room now." It's instantaneous.

But decreasing the size? That’s a whole different animal.

If you try to shrink a column, SQL Server has to scan every single row to ensure the existing data won't be truncated. If it finds even one string that’s 51 characters long while you’re trying to move to VARCHAR(50), the whole transaction rolls back. It’s a safety feature, but a heavy one.

The Hidden Danger of Fixed-Width Types

While VARCHAR is relatively forgiving, fixed-width types like CHAR, INT, or DECIMAL are brutal. If you change a CHAR(10) to a CHAR(20), SQL Server has to physically rewrite every row on every page to account for the new padding.

Think about your transaction log.

Every single one of those rewrites is logged. If you're doing this on a high-traffic system with Always On Availability Groups, you’re now pushing Gigs of log data across the network to your secondary replicas. You might see your "redo queue" spike, and suddenly your high-availability setup isn't so "available" anymore because the secondary is struggling to keep up.

Real-World Horror: The Off-Row Data Problem

I once watched a team try to change an ms sql alter column size on a table that used NVARCHAR(MAX). They thought it would be fine because it’s a LOB (Large Object) type.

They were wrong.

When you modify columns that involve off-row storage, SQL Server's internal pointer system gets complicated. If you're moving from a variable-length type to something else, or if the change pushes the row size past the 8,060-byte limit for in-row data, SQL Server starts pushing data to "Row-Overflow" pages. This fragmentation can kill your read performance. You’ll end up with a database that’s technically correct but practically unusable because every SELECT * now requires three times the I/O.

Dealing with Indexes and Constraints

You can't just alter a column if it’s participating in an index. SQL Server will throw a 5074 error faster than you can blink.

"The index 'IX_YourIndex' is dependent on column 'YourColumn'."

This is where the "simple" change becomes a 50-line script. You have to:

1. Identify all indexes using the column.
2. Drop them.
3. Perform the ms sql alter column size change.
4. Recreate the indexes.

If that column is a Primary Key or part of a Foreign Key constraint? You're in for a long night. Dropping a Primary Key constraint to change a column size means you also have to drop every Foreign Key in other tables that points to it.

It’s like pulling a loose thread on a sweater. Before you know it, the whole sleeve is gone.

Performance Tuning Your Alter

If you absolutely must change a column size on a massive table and a metadata-only change isn't an option, stop using ALTER TABLE.

Instead, consider the "Shadow Table" approach.
Basically, you create a brand new table with the correct schema. You then migrate the data in batches—maybe 10,000 rows at a time. This keeps your transaction log growth under control and avoids a single, massive table lock that lasts for four hours. Once the data is synced, you use sp_rename to swap the tables. It’s more manual work, but it’s the professional way to handle high-concurrency environments.

Another trick: if you're on Enterprise Edition, check if your table uses Data Compression. Changing column sizes on compressed tables adds another layer of CPU overhead. Sometimes it's faster to decompress, alter, and re-compress, though that's a lot of I/O.

Precision and Scale: The Decimal Trap

Changing the size of a DECIMAL or NUMERIC column is particularly prickly. If you change the precision (the total number of digits) or the scale (the digits to the right of the decimal point), you are almost always triggering a full table rewrite.

$DECIMAL(10,2)$ vs $DECIMAL(12,2)$

Even though you’re just adding room for larger numbers, the internal storage format changes. Don't do this during peak hours. Just don't.

Best Practices for the Weary DBA

First, always check the dependencies. Use sys.dm_sql_referenced_entities to see what stored procedures or views might break if the column size changes. If a view was created with SCHEMABINDING, your ALTER will fail.

Second, test the timing on a restored copy of production. Don't guess. If the alter takes 20 minutes on your dev machine with 1,000 rows, it won't take 20 minutes on prod with 10 million.

Third, monitor your tempdb. Large alters often use tempdb for sorting or intermediate storage. If tempdb runs out of space, your transaction fails, and the rollback could take twice as long as the initial attempt.

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Practical Steps to Take Right Now

If you're staring at a "String or binary data would be truncated" error and need to perform an ms sql alter column size change:

• Check for NULLs: Ensure your ALTER statement explicitly defines NULL or NOT NULL to match the current schema.
• Review Indexes: Use a script to find all indexes tied to that column. You'll need to script their creation before dropping them.
• Log Space: Ensure your transaction log has enough room to grow, or perform the change in a simple recovery model if your business requirements allow it (rare for prod, but helpful for migrations).
• Batching: For truly massive tables, skip the ALTER command and use a staging table to migrate data in chunks.
• Verify: After the change, run DBCC CHECKTABLE to ensure no corruption occurred during the rewrite, especially if the operation was interrupted.

Don't treat database schema changes like code changes. Code is ephemeral; data has mass. Moving it takes effort and energy. Respect the lock, watch the log, and always have a rollback plan that doesn't involve "praying to the backup gods."

Most of the time, a simple ALTER works fine. But being a pro means knowing exactly when "fine" is about to turn into a "Sev 1" outage. Keep your scripts clean, your backups fresh, and your precision high.