Identity Value Exhaustion in SQL Server (and how not to get paged at 2am 😅)

Written By Rich Benner

If you’ve worked with identity columns in Microsoft SQL Server, you’ve probably treated them like oxygen: always there, never think about it.

…until one day inserts start failing with:

Arithmetic overflow error converting IDENTITY to data type int.

Cannot insert explicit value for identity column...

And suddenly your “infinite” IDs are very, very finite.

This is identity value exhaustion, and it’s 100% preventable if you know what to watch for.

Let’s walk through:

  • What it is

  • How it happens

  • How to detect it early

  • How to fix it safely

  • How to design so it never happens again

  • Demo scripts along the way

Casual, practical, copy pasteable. Let’s go.

Quick refresher: what’s an IDENTITY?

Typical table:

CREATE TABLE dbo.Orders
(
    OrderId INT IDENTITY(1,1) PRIMARY KEY,
    OrderDate DATETIME2 NOT NULL DEFAULT sysdatetime()
);

IDENTITY(1,1) means:

  • start at 1

  • increment by 1

  • SQL Server auto-generates values

But here’s the catch:

👉 The data type limits the range, not SQL Server magic.

Type Max value
TINYINT 255
SMALLINT 32,767
INT 2,147,483,647
BIGINT 9,223,372,036,854,770,000

If you hit the max… inserts fail. Hard stop. No wrap around.

How identity exhaustion happens in real life

It’s rarely “we actually inserted 2 billion rows.”

More common causes:

1. Frequent deletes

Burns numbers faster than you think.

2. Rollbacks

Identity values are not transactional. They’re consumed even if the transaction rolls back.

BEGIN TRAN;

INSERT dbo.Orders DEFAULT VALUES;

ROLLBACK;

In this scenario, the identity value would still be consumed.

3. High-volume logging/event tables

Millions per day → exhaustion sneaks up fast.

4. Bad initial design

Using INT when BIGINT should’ve been obvious.

Classic “we didn’t think this app would still be alive in 10 years” problem.

How to check if you’re in danger

Here’s a handy script to see identity usage:

Check identity headroom

CREATE TABLE #IdentityExhaustion
(
 DatabaseName sysname
,SchemaName sysname
,TableName sysname
,IdentityColumn sysname
,seed_value sql_variant
,increment_value sql_variant
,last_value sql_variant
,max_value sql_variant
,PercentUsed DECIMAL(10,7)
)

EXEC sp_MSforeachdb N'
USE [?]
DECLARE @PercentOfMax BIGINT = ''50''
INSERT INTO #IdentityExhaustion (DatabaseName,SchemaName,TableName,IdentityColumn,seed_value,increment_value,last_value,max_value,PercentUsed)
SELECT
    DB_NAME() AS DatabaseName,
	s.name AS SchemaName,
	t.name AS TableName,
    c.name AS IdentityColumn,
    ic.seed_value,
    ic.increment_value,
    ic.last_value,
    CASE ty.name
        WHEN ''tinyint'' THEN 255
        WHEN ''smallint'' THEN 32767
        WHEN ''int'' THEN 2147483647
        WHEN ''bigint'' THEN 9223372036854775807
    END AS MaxValue,
    100.0 * CONVERT(bigint,ic.last_value) /
    CASE ty.name
        WHEN ''tinyint'' THEN 255
        WHEN ''smallint'' THEN 32767
        WHEN ''int'' THEN 2147483647
        WHEN ''bigint'' THEN 9223372036854775807
    END AS PercentUsed
FROM sys.identity_columns ic
JOIN sys.tables t ON ic.object_id = t.object_id
JOIN sys.schemas s ON t.schema_id = s.schema_id
JOIN sys.columns c ON ic.object_id = c.object_id AND ic.column_id = c.column_id
JOIN sys.types ty ON c.user_type_id = ty.user_type_id
WHERE (ty.name = ''tinyint'' AND (CONVERT(bigint,ic.last_value)) >= (255 * (@PercentOfMax/100.0)))
OR (ty.name = ''smallint'' AND (CONVERT(bigint,ic.last_value)) >= (32767 * (@PercentOfMax/100.0)))
OR (ty.name = ''int'' AND (CONVERT(bigint,ic.last_value)) >= (2147483647 * (@PercentOfMax/100.0)))
OR (ty.name = ''bigint'' AND (CONVERT(bigint,ic.last_value)) >= (9223372036854775807 * (@PercentOfMax/100.0)))'

SELECT * 
FROM #IdentityExhaustion
ORDER BY PercentUsed DESC

DROP TABLE #IdentityExhaustion

 Fix options (from “quick patch” to “grown-up solution”)

Option 1 — Change to BIGINT (best long-term fix)

This is the adult answer.

For larger tables, you don’t want to modify this data type in-place, it’ll take a while and it’s a great way to blow out your transaction log. The better approach is to create a new copy of the table with the data types you’re after and switch it with your live table.

Steps:

1. Create a copy of your table

You’ll want an exact copy of your table structure including any indexes and constraints with the priority being that you need to update the data type of your identity column. Name this table something simple, like TableName_New.

It’s worth noting, you will have to add a suffix to all of your indexes and constraints too, we’ll rename these after.

2. Copy Data

We’ll then want to create a script that will copy our data from the original table to the new one.

We’re going to be inserting data into an identity column, so you will need to enable identity insert

SET IDENTITY_INSERT [TableName] ON

How large your batches are is completely up to you, but that will depend upon the hardware you’re working with and your specific workloads.

For reference, I recently moved a table with 2 billion rows by doing batches of 1 million, that took about 19 hours to complete.

3. Insert, Update, Delete Trigger

As you’re copying your data you’re going to want to keep it up to date too.

Write yourself a trigger that will send any data changes to your new table, this will save you a lot of pain and time at cutover.

4. Consider Foreign Keys

Use sp_fkeys on your existing table, if there are any foreign keys pointing towards it you’re going to want to drop those and recreate after the cutover.

5. sp_rename

Once all of your data is transferred over and the trigger is keeping it maintained, we’re good to switch our tables.

Use sp_rename to change your live table name to add a suffix, something like “_OLD”

Use sp_rename again to remove the suffix from your “_New” table

You should now have your table with the bigint value in place of your original table and with the same data.

6. Cleanup
Go ahead and turn identity insert off again, we don’t want that hanging around causing problems.

SET IDENTITY_INSERT [TableName] OFF

We’ll also want to re-apply those foreign keys (and make sure we run the check command on them)

Once we’re happy that the switch has been successful and the new table contains the data we need, we’re golden.

You can then delete your _OLD table whenever you feel confident to do so.

Option 2 — Truncate Table

This is only an option if you don’t care about the data inside your table.

Running a truncate command on the table will deallocate all data pages associated to that table, it nukes it, you will lose all data.

However, what it also does is reset your IDENTITY column to its original seed which immediately solves our problem.

This is extremely useful for tables that are used in ETL processes or otherwise for logging data that we don’t need to keep long term.

Very situational, but a solution to this problem.

Option 3 — Reseed

Only works if you still have space left.

DBCC CHECKIDENT('dbo.Orders', RESEED, 1000000);

Useful when:

  • you bulk deleted rows

  • you want to jump ahead

BUT:

Does NOT increase max range.

Option 3 — Negative reseed trick (emergency hack)

If you’re desperate:

DBCC CHECKIDENT ('dbo.Orders', RESEED, -1);

DBCC CHECKIDENT('dbo.Orders', RESEED, -1);

Now it goes negative:

-1, -2, -3...

Buys time.

But:

  • ugly

  • confusing

  • breaks assumptions

  • tech debt city

Use only if prod is on fire.



That should give you a few options on how to get out of trouble.

If you’re in this hole and in over your head, feel free to contact us for an assist

Rich Benner
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