Online Schema Changes

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CockroachDB's online schema changes provide a simple way to update a table schema without imposing any negative consequences on an application — including downtime. The schema change engine is a built-in feature requiring no additional tools, resources, or ad hoc sequencing of operations.

Benefits of online schema changes include:

  • Changes to your table schema happen while the database is running.
  • The schema change runs as a background job without holding locks on the underlying table data.
  • Your application's queries can run normally, with no effect on read/write latency. The schema is cached for performance.
  • Your data is kept in a safe, consistent state throughout the entire schema change process.

Schema changes consume additional resources, and if they are run when the cluster is near peak capacity, latency spikes can occur. This is especially true for any schema change that adds columns, drops columns, or adds an index. We do not recommend doing more than one schema change at a time while in production.


CockroachDB does not support schema changes within explicit transactions with full atomicity guarantees. CockroachDB only supports DDL changes within implicit transactions (individual statements). If a schema management tool uses transactions on your behalf, it should only execute one schema change operation per transaction.

How online schema changes work

At a high level, online schema changes are accomplished by using a bridging strategy involving concurrent uses of multiple versions of the schema. The process is as follows:

  1. You initiate a schema change by executing ALTER TABLE, CREATE INDEX, TRUNCATE, etc.

  2. The schema change engine converts the original schema to the new schema in discrete steps while ensuring that the underlying table data is always in a consistent state. These changes are executed as a background job, and can be paused, resumed, and canceled.

This approach allows the schema change engine to roll out a new schema while the previous version is still in use. It then backfills or deletes the underlying table data as needed in the background, while the cluster is still running and servicing reads and writes from your application.

During the backfilling process, the schema change engine updates the underlying table data to make sure all instances of the table are stored according to the requirements of the new schema.

Once backfilling is complete, all nodes will switch over to the new schema, and will allow reads and writes of the table using the new schema.

For more technical details, see How online schema changes are possible in CockroachDB.

The following online schema changes pause if the node executing the schema change is running out of disk space:


If a schema change job is paused, any jobs waiting on that schema change will stop waiting and return an error.


If a schema change fails, the schema change job will be cleaned up automatically. However, there are limitations with rolling back schema changes within a transaction; for more information, see Schema change DDL statements inside a multi-statement transaction can fail while other statements succeed.

For advice about how to avoid running out of space during an online schema change, refer to Estimate your storage capacity before performing online schema changes.

Declarative schema changer

CockroachDB only guarantees atomicity for schema changes within single statement transactions, either implicit transactions or in an explicit transaction with a single schema change statement. The declarative schema changer is the next iteration of how schema changes will be performed in CockroachDB. By planning schema change operations in a more principled manner, the declarative schema changer will ultimately make transactional schema changes possible. You can identify jobs that are using the declarative schema changer by running SHOW JOBS and finding jobs with a job_type of NEW SCHEMA CHANGE.

The following statements use the declarative schema changer by default:

Until all schema change statements are moved to use the declarative schema changer you can enable and disable the declarative schema changer for supported statements using the sql.defaults.use_declarative_schema_changer cluster setting and the use_declarative_schema_changer session variable.


Declarative schema changer statements and legacy schema changer statements operating on the same objects cannot exist within the same transaction. Either split the transaction into multiple transactions, or disable the cluster setting or session variable.


Use ALTER ROLE ALL SET {sessionvar} = {val} instead of the sql.defaults.* cluster settings. This allows you to set a default value for all users for any session variable that applies during login, making the sql.defaults.* cluster settings redundant.

Best practices for online schema changes

Estimate your storage capacity before performing online schema changes

Some schema change operations, like adding or dropping columns or altering primary keys, will temporarily increase a cluster's storage consumption. Specifically, these operations may temporarily require up to three times more storage space for the range size while the schema change is being applied, and this may cause the cluster to run out of storage space or fail to apply the schema change.

To estimate the size of the indexes in your table, use the SHOW RANGES statement.


The output includes a range_size_mb column that shows the size of the range in megabytes for each index.

In many cases this range size is trivial, but when the range size is many gigabytes or terabytes, you will need at least three times that amount of free storage space to successfully apply an online schema change.

Example of finding the range size of an index

  1. Start a 3 node cockroach demo cluster with the MovR dataset.

    cockroach demo --nodes 3
  2. Turn off the deprecated behavior of SHOW RANGES:

    SET CLUSTER SETTING sql.show_ranges_deprecated_behavior.enabled TO 'false';
  3. Find the range size of the indexes in the movr.vehicles table:

    WITH x AS (
    SELECT index_name,
           round(range_size_mb, 4) as range_size_mb
      FROM x;
                  index_name               | range_size_mb
      vehicles_pkey                         |        0.0005
      vehicles_pkey                         |        0.0002
      vehicles_pkey                         |        0.0005
      vehicles_pkey                         |        0.0006
      vehicles_pkey                         |        0.0002
      vehicles_pkey                         |        0.0002
      vehicles_pkey                         |        0.0002
      vehicles_pkey                         |        0.0002
      vehicles_pkey                         |        0.0103
      vehicles_auto_index_fk_city_ref_users |        0.0103
    (10 rows)

Run schema changes with large backfills during off-peak hours

Online schema changes that result in large backfill operations (for example, ALTER TABLE ... ALTER COLUMN statements) are computationally expensive, and can result in degraded performance. The admission control system will help keep high-priority operations running, but it's recommended to run backfill-heavy schema changes during times when the cluster is under relatively low loads.

Schema changes in multi-region clusters

To reduce latency while making online schema changes, we recommend specifying a lease_preference zone configuration on the system database to a single region and running all subsequent schema changes from a node within that region. For example, if the majority of online schema changes come from machines that are geographically close to us-east1, run the following:

ALTER DATABASE system CONFIGURE ZONE USING constraints = '{"+region=us-east1": 1}', lease_preferences = '[[+region=us-east1]]';

Run all subsequent schema changes from a node in the specified region.

If you do not intend to run more schema changes from that region, you can safely remove the lease preference from the zone configuration for the system database.



For more examples of schema change statements, see the ALTER TABLE subcommands.

Run schema changes inside a transaction with CREATE TABLE

As noted in Limitations, you cannot run schema changes inside transactions in general.

However, you can run schema changes inside the same transaction as a CREATE TABLE statement. For example:

  SAVEPOINT cockroach_restart;
  CREATE TABLE fruits (
        id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
        name STRING,
        color STRING
  INSERT INTO fruits (name, color) VALUES ('apple', 'red');
  ALTER TABLE fruits ADD COLUMN inventory_count INTEGER DEFAULT 5;
  ALTER TABLE fruits ADD CONSTRAINT name CHECK (name IN ('apple', 'banana', 'orange'));
  SELECT name, color, inventory_count FROM fruits;
  RELEASE SAVEPOINT cockroach_restart;

The transaction succeeds with the following output:

| name  | color | inventory_count |
| apple | red   |               5 |
(1 row)

Run multiple schema changes in a single ALTER TABLE statement

Some schema changes can be used in combination in a single ALTER TABLE statement. For a list of commands that can be combined, see ALTER TABLE. For a demonstration, see Add and rename columns atomically.

Show all schema change jobs

You can check on the status of the schema change jobs on your system at any time using the SHOW JOBS statement:

|             job_id | job_type      | description                                                                 | user_name | status    | created                    | started                    | finished                   | modified                   | fraction_completed | error | coordinator_id |
| 368863345707909121 | SCHEMA CHANGE | ALTER TABLE test.public.fruits ADD COLUMN inventory_count INTEGER DEFAULT 5 | root      | succeeded | 2018-07-26 20:55:59.698793 | 2018-07-26 20:55:59.739032 | 2018-07-26 20:55:59.816007 | 2018-07-26 20:55:59.816008 |                  1 |       | NULL           |
| 370556465994989569 | SCHEMA CHANGE | ALTER TABLE ADD COLUMN bar VARCHAR                          | root      | pending   | 2018-08-01 20:27:38.708813 | NULL                       | NULL                       | 2018-08-01 20:27:38.708813 |                  0 |       | NULL           |
| 370556522386751489 | SCHEMA CHANGE | ALTER TABLE ADD COLUMN bar VARCHAR                          | root      | pending   | 2018-08-01 20:27:55.830832 | NULL                       | NULL                       | 2018-08-01 20:27:55.830832 |                  0 |       | NULL           |
(1 row)

All schema change jobs can be paused, resumed, and canceled.

Demo videos

Updating primary key columns

To see a demo of an online schema change against a primary key column, watch the following video:

Updating foreign key columns

To see a demo of an online schema change against a foreign key column, watch the following video:

Undoing a schema change

Prior to garbage collection, it's possible to recover data that may have been lost prior to schema changes by using the AS OF SYSTEM TIME parameter. However, this solution is limited in terms of time, and doesn't work beyond the designated garbage collection window.

For more long-term recovery solutions, consider taking either a full or incremental backup of your cluster.


Schema changes within transactions

Most schema changes should not be performed within an explicit transaction with multiple statements, as they do not have the same atomicity guarantees as other SQL statements. Execute schema changes either as single statements (as an implicit transaction), or in an explicit transaction consisting of the single schema change statement. There are some exceptions to this, detailed below.

Schema changes keep your data consistent at all times, but they do not run inside transactions in the general case. Making schema changes transactional would mean requiring a given schema change to propagate across all the nodes of a cluster. This would block all user-initiated transactions being run by your application, since the schema change would have to commit before any other transactions could make progress. This would prevent the cluster from servicing reads and writes during the schema change, requiring application downtime.

Some schema change operations can be run within explicit, multiple statement transactions. CREATE TABLE and CREATE INDEX statements can be run within the same transaction with the same atomicity guarantees as other SQL statements. There are no performance or rollback issues when using these statements within a multiple statement transaction.

Within a single transaction:


If a schema change within a transaction fails, manual intervention may be needed to determine which statement has failed. After determining which schema change(s) failed, you can then retry the schema change.

Schema change DDL statements inside a multi-statement transaction can fail while other statements succeed

Most schema change DDL statements that run inside a multi-statement transaction with non-DDL statements can fail at COMMIT time, even if other statements in the transaction succeed. This leaves such transactions in a "partially committed, partially aborted" state that may require manual intervention to determine whether the DDL statements succeeded.

Some DDL statements do not have this limitation. CREATE TABLE and CREATE INDEX statements have the same atomicity guarantees as other statements within a transaction.

If such a failure occurs, CockroachDB will emit a CockroachDB-specific error code, XXA00, and the following error message:

transaction committed but schema change aborted with error: <description of error>
HINT: Some of the non-DDL statements may have committed successfully, but some of the DDL statement(s) failed.
Manual inspection may be required to determine the actual state of the database.

If you must execute schema change DDL statements inside a multi-statement transaction, we strongly recommend checking for this error code and handling it appropriately every time you execute such transactions.

This error will occur in various scenarios, including but not limited to:

  • Creating a unique index fails because values aren't unique.
  • The evaluation of a computed value fails.
  • Adding a constraint (or a column with a constraint) fails because the constraint is violated for the default/computed values in the column.

To see an example of this error, start by creating the following table.

INSERT INTO T(x) VALUES (1), (2), (3);

Then, enter the following multi-statement transaction, which will trigger the error.

pq: transaction committed but schema change aborted with error: (23505): duplicate key value (x)=(3) violates unique constraint "unique_x"
HINT: Some of the non-DDL statements may have committed successfully, but some of the DDL statement(s) failed.
Manual inspection may be required to determine the actual state of the database.

In this example, the INSERT statement committed, but the ALTER TABLE statement adding a UNIQUE constraint failed. We can verify this by looking at the data in table t and seeing that the additional non-unique value 3 was successfully inserted.

(4 rows)

No online schema changes if primary key change in progress

You cannot start an online schema change on a table if a primary key change is currently in progress on the same table.

No online schema changes between executions of prepared statements

When the schema of a table targeted by a prepared statement changes after the prepared statement is created, future executions of the prepared statement could result in an error. For example, adding a column to a table referenced in a prepared statement with a SELECT * clause will result in an error:

INSERT INTO users VALUES (1, 'Max Roach');
EXECUTE prep1;
ERROR: cached plan must not change result type

It's therefore recommended to explicitly list result columns instead of using SELECT * in prepared statements, when possible.

ALTER TYPE schema changes cannot be cancelled

You can only cancel ALTER TYPE schema change jobs that drop values. All other ALTER TYPE schema change jobs are non-cancellable.

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