Delta Migration from MySQL

A uses an initial data load, followed by , to . In this approach, you migrate most application data to the target using before stopping application traffic to the source database. You then use to keep the target database in sync with any changes in the source database (the migration delta), before finally halting traffic to the source and cutting over to the target after schema finalization and data verification.

• All source data is migrated to the target .

• This approach utilizes .

• is supported, though this example will not use it. See for an example of a migration that uses failback replication.

This approach is best for production environments that need to .

This page describes an example scenario. While the commands provided can be copy-and-pasted, they may need to be altered or reconsidered to suit the needs of your specific environment.

Example scenario

You have a small (300 GB) database that provides the data store for a web application. You want to migrate the entirety of this database to a new CockroachDB cluster. Business cannot accommodate a full maintenance window, but it can accommodate a brief (<60 second) halt in traffic.

The application runs on a Kubernetes cluster.

Estimated system downtime: 3-5 minutes.

Before the migration

• Install the tools.
• Review the and documentation.
• and .
• Recommended: Perform a dry run of this full set of instructions in a development environment that closely resembles your production environment. This can help you get a realistic sense of the time and complexity it requires.
• Understand the prerequisites and limitations of the MOLT tools:

Limitations

MOLT Fetch limitations

• Only tables with types of , , or can be sharded with .
• GEOMETRY and GEOGRAPHY types are not supported.

MOLT Replicator limitations

• Replication modes require connection to the primary instance (PostgreSQL primary, MySQL primary/master, or Oracle primary). MOLT cannot obtain replication checkpoints or transaction metadata from replicas.

• Running DDL on the source or target while replication is in progress can cause replication failures.

• TRUNCATE operations on the source are not captured. Only INSERT, UPDATE, UPSERT, and DELETE events are replicated.

• Changes to virtual columns are not replicated automatically. To migrate these columns, you must define them explicitly with .

• MySQL replication is supported only with GTID-based configurations. Binlog-based features that do not use GTID are not supported.

MOLT Verify limitations

• MOLT Verify compares 20,000 rows at a time by default, and row values can change between batches, potentially resulting in temporary inconsistencies in data. To configure the row batch size, use the --row_batch_size .

• MOLT Verify checks for collation mismatches on columns. This may cause validation to fail when a is used as a primary key and the source and target databases are using different .

• MOLT Verify might give an error in case of schema changes on either the source or target database.

• cannot yet be compared.

• MOLT Verify only supports comparing one MySQL database to a whole CockroachDB schema (which is assumed to be public).

Step 1: Prepare the source database

In this step, you will:

• Create a dedicated migration user on your source database.
• Configure the source database for replication.

Create migration user on source database

Create a dedicated migration user (for example, MIGRATION_USER) on the source database. This user is responsible for reading data from source tables during the migration. You will pass this username in the source connection string.

CREATE USER 'migration_user'@'%' IDENTIFIED BY 'password';

Grant the user privileges to select the tables you migrate and access GTID information for snapshot consistency:

GRANT SELECT ON migration_db.* TO 'migration_user'@'%';
GRANT SELECT ON mysql.gtid_executed TO 'migration_user'@'%';
FLUSH PRIVILEGES;

For replication, grant additional privileges for binlog access:

GRANT REPLICATION SLAVE, REPLICATION CLIENT ON *.* TO 'migration_user'@'%';
FLUSH PRIVILEGES;

Configure source database for replication

Connect to the primary instance (PostgreSQL primary, MySQL primary/master, or Oracle primary), not a replica. Replicas cannot provide the necessary replication checkpoints and transaction metadata required for ongoing replication.

Enable global transaction identifiers (GTID) and configure binary logging. Set binlog-row-metadata or binlog-row-image to full to provide complete metadata for replication.

Configure binlog retention to ensure GTIDs remain available throughout the migration:

• MySQL 8.0.1+: Set binlog_expire_logs_seconds (default: 2592000 = 30 days) based on your migration timeline.
• MySQL < 8.0: Set expire_logs_days, or manually manage retention by setting max_binlog_size and using PURGE BINARY LOGS BEFORE NOW() - INTERVAL 1 HOUR (adjusting the interval as needed). Force binlog rotation with FLUSH BINARY LOGS if needed.
• Managed services: Refer to provider-specific configuration for Amazon RDS or Google Cloud SQL.

GTID replication sends all database changes to Replicator. To limit replication to specific tables or schemas, apply a userscript when you run Replicator. Refer to the cookbook example.

Version	Configuration
MySQL 5.6	--gtid-mode=on --enforce-gtid-consistency=on --server-id={unique_id} --log-bin=mysql-binlog --binlog-format=row --binlog-row-image=full --log-slave-updates=ON
MySQL 5.7	--gtid-mode=on --enforce-gtid-consistency=on --binlog-row-image=full --server-id={unique_id} --log-bin=log-bin
MySQL 8.0+	--gtid-mode=on --enforce-gtid-consistency=on --binlog-row-metadata=full
MariaDB	--log-bin --server_id={unique_id} --log-basename=master1 --binlog-format=row --binlog-row-metadata=full

Step 2: Prepare the target database

Define the target tables

Convert the source table definitions into CockroachDB-compatible equivalents. CockroachDB supports the PostgreSQL wire protocol and is largely .

• The source and target table definitions must match. Review to understand which source types can be mapped to CockroachDB types.

  MySQL tables belong directly to the database specified in the connection string. A MySQL source table defined as CREATE TABLE tbl (id INT PRIMARY KEY); should map to CockroachDB’s default public schema:

  CREATE TABLE tbl (id INT PRIMARY KEY);
  

  • MOLT Fetch can automatically define matching CockroachDB tables using the option.

  • If you define the target tables manually, review how MOLT Fetch handles . You can use the MOLT Schema Conversion Tool to create matching table definitions.

• Every table must have an explicit primary key.

  Avoid using sequential keys. To learn more about the performance issues that can result from their use, refer to the . If a sequential key is necessary in your CockroachDB table, you must create it manually, after using to load and replicate the data.

• Review to understand how computed columns and partitioned tables can be mapped to the target, and how target tables can be renamed.

• By default on CockroachDB, INT is an alias for INT8, which creates 64-bit signed integers. PostgreSQL and MySQL default to 32-bit integers. Depending on your source database or application requirements, you may need to change the integer size to 4. For more information, refer to .

Schema Conversion Tool

The (SCT) converts source table definitions to CockroachDB-compatible syntax. It requires a free .

1. Upload a source .sql file to convert the syntax and identify in the table definitions.

2. Import the converted table definitions to a CockroachDB cluster:

   • When migrating to CockroachDB Cloud, the Schema Conversion Tool automatically .
   • When migrating to a self-hosted CockroachDB cluster, and pipe the directly into .

Syntax that cannot automatically be converted will be displayed in the . These may include the following:

String case sensitivity

Strings are case-insensitive in MySQL and case-sensitive in CockroachDB. You may need to edit your MySQL data to get the results you expect from CockroachDB. For example, you may have been doing string comparisons in MySQL that will need to be changed to work with CockroachDB.

For more information about the case sensitivity of strings in MySQL, refer to Case Sensitivity in String Searches from the MySQL documentation. For more information about CockroachDB strings, refer to .

Identifier case sensitivity

Identifiers are case-sensitive in MySQL and . When , you can either keep case sensitivity by enclosing identifiers in double quotes, or make identifiers case-insensitive by converting them to lowercase.

AUTO_INCREMENT attribute

The MySQL AUTO_INCREMENT attribute, which creates sequential column values, is not supported in CockroachDB. When , columns with AUTO_INCREMENT can be converted to use , UUID values with , or unique INT8 values using . Cockroach Labs does not recommend using a sequence to define a primary key column. For more information, refer to .

Changing a column type during table definition conversion will cause to identify a type mismatch during data validation. This is expected behavior.

ENUM type

MySQL ENUM types are defined in table columns. On CockroachDB, is a standalone type. When , you can either deduplicate the ENUM definitions or create a separate type for each column.

TINYINT type

TINYINT data types are not supported in CockroachDB. The automatically converts TINYINT columns to (SMALLINT).

Geospatial types

MySQL geometry types are not converted to CockroachDB by the . They should be manually converted to the corresponding types in CockroachDB.

FIELD function

The MYSQL FIELD function is not supported in CockroachDB. Instead, you can use the function, which returns the index of the first occurrence of element in the array.

Example usage:

SELECT array_position(ARRAY[4,1,3,2],1);

  array_position
------------------
               2
(1 row)

While MySQL returns 0 when the element is not found, CockroachDB returns NULL. So if you are using the ORDER BY clause in a statement with the array_position function, the caveat is that sort is applied even when the element is not found. As a workaround, you can use the operator.

SELECT * FROM table_a ORDER BY COALESCE(array_position(ARRAY[4,1,3,2],5),999);

Drop constraints and indexes

To optimize data load performance, drop all non-PRIMARY KEY and on the target CockroachDB database before migrating:

• (you do not need to drop this constraint when using drop-on-target-and-recreate for table handling)

Do not drop constraints.

You can recreate the constraints and indexes after loading the data.

Create the SQL user

Create a SQL user in the CockroachDB cluster that has the necessary privileges.

To create a user crdb_user in the default database (you will pass this username in the target connection string):

CREATE USER crdb_user WITH PASSWORD 'password';

Grant database-level privileges for schema creation within the target database:

GRANT ALL ON DATABASE defaultdb TO crdb_user;

Grant permission to modify cluster settings:

GRANT SYSTEM MODIFYCLUSTERSETTING TO crdb_user;

Grant usage on schemas being migrated:

GRANT USAGE ON SCHEMA migration_schema TO crdb_user;
GRANT USAGE ON SCHEMA public TO crdb_user;

Grant user privileges to create tables in the migration_schema schema and internal MOLT tables like _molt_fetch_exceptions in the public CockroachDB schema:

Ensure that you are connected to the target database.

GRANT CREATE ON SCHEMA migration_schema TO crdb_user;
GRANT CREATE ON SCHEMA public TO crdb_user;

If you manually defined the target tables (which means that drop-on-target-and-recreate will not be used), grant the following privileges on the schema:

GRANT SELECT, INSERT, UPDATE, DELETE ON ALL TABLES IN SCHEMA public TO crdb_user;
ALTER DEFAULT PRIVILEGES IN SCHEMA public
GRANT SELECT, INSERT, UPDATE, DELETE ON TABLES TO crdb_user;

If you will be running Fetch with drop-on-target-and-recreate, and the target schema has pre-existing tables that were created by a different user, you may need to change table ownership to allow the migration user to drop those tables. Make the following alteration for each table:

ALTER TABLE migration_schema.table1 OWNER TO crdb_user;

Depending on the MOLT Fetch you will use, grant the necessary privileges to run either IMPORT INTO or COPY FROM on the target tables:

IMPORT INTO privileges

Grant SELECT, INSERT, and DROP (required because the table is taken offline during the IMPORT INTO) privileges on all tables being migrated:

GRANT SELECT, INSERT, DROP ON ALL TABLES IN SCHEMA public TO crdb_user;

If you plan to use cloud storage with implicit authentication for data load, grant the EXTERNALIOIMPLICITACCESS :

GRANT SYSTEM EXTERNALIOIMPLICITACCESS TO crdb_user;

COPY FROM privileges

Grant privileges to the user:

GRANT admin TO crdb_user;

Set session variable

Ensure that the statement_timeout is set to 0s for the user:

ALTER ROLE crdb_user SET statement_timeout = '0s';

Replication privileges

Grant permissions to create the staging schema for replication:

ALTER USER crdb_user CREATEDB;

Configure GC TTL

Before starting the initial data load, configure the on the source CockroachDB cluster to ensure that historical data remains available when replication begins. The GC TTL must be long enough to cover the full duration of the data load.

Increase the GC TTL before starting the data load. For example, to set the GC TTL to 24 hours:

ALTER DATABASE defaultdb CONFIGURE ZONE USING gc.ttlseconds = 86400;

The GC TTL duration must be higher than your expected time for the initial data load.

Once replication has started successfully (which automatically protects its own data range), you can restore the GC TTL to its original value. For example, to restore to 5 minutes:

ALTER DATABASE defaultdb CONFIGURE ZONE USING gc.ttlseconds = 300;

For details, refer to .

Step 3: Load data into CockroachDB

In this step, you will:

• Configure MOLT Fetch with the flags needed for your migration.
• Run MOLT Fetch.
• Understand how to continue a load after an interruption.

Configure MOLT Fetch

The includes detailed information about how to , and how to .

When you run molt fetch, you can configure the following options for data load:

• : Specify URL‑encoded source and target connections.
• : Specify schema and table names to migrate.
• : Export data to cloud storage or a local file server.
• : Specifies whether data will only be loaded into/from intermediate storage.
• : Divide larger tables into multiple shards during data export.
• : Choose between IMPORT INTO and COPY FROM.
• : Determine how existing target tables are initialized before load.
• : Define any row-level transformations to apply to the data before it reaches the target.
• : Configure metrics collection during initial data load.

Read through the documentation to understand how to configure your molt fetch command and its flags. Follow , especially those related to security.

At minimum, the molt fetch command should include the source, target, data path, and flags:

molt fetch \
--source $SOURCE \
--target $TARGET \
--bucket-path 's3://bucket/path' \
--ignore-replication-check

However, depending on the needs of your migration, you may have many more flags set, and you may need to prepare some accompanying .json files.

Run MOLT Fetch

Perform the initial load of the source data.

1. Issue the command to move the source data to CockroachDB. This example command passes the source and target connection strings as environment variables, writes intermediate files to S3 storage, and uses the truncate-if-exists table handling mode to truncate the target tables before loading data. It also limits the migration to a single schema and filters three specific tables to migrate. The defaults to IMPORT INTO.

   molt fetch \
   --source $SOURCE \
   --target $TARGET \
   --table-filter 'employees|payments|orders' \
   --bucket-path 's3://migration/data/cockroach' \
   --table-handling truncate-if-exists
   

2. Check the output to observe fetch progress.

   A starting fetch message indicates that the task has started:

   {"level":"info","type":"summary","num_tables":3,"cdc_cursor":"4c658ae6-e8ad-11ef-8449-0242ac140006:1-29","time":"2025-02-10T14:28:11-05:00","message":"starting fetch"}
   

   data extraction messages are written for each table that is exported to the location in --bucket-path:

   {"level":"info","table":"public.employees","time":"2025-02-10T14:28:11-05:00","message":"data extraction phase starting"}
   
   {"level":"info","table":"public.employees","type":"summary","num_rows":200000,"export_duration_ms":1000,"export_duration":"000h 00m 01s","time":"2025-02-10T14:28:12-05:00","message":"data extraction from source complete"}
   

   data import messages are written for each table that is loaded into CockroachDB:

   {"level":"info","table":"public.employees","time":"2025-02-10T14:28:12-05:00","message":"starting data import on target"}
   
   {"level":"info","table":"public.employees","type":"summary","net_duration_ms":1899.748333,"net_duration":"000h 00m 01s","import_duration_ms":1160.523875,"import_duration":"000h 00m 01s","export_duration_ms":1000,"export_duration":"000h 00m 01s","num_rows":200000,"cdc_cursor":"4c658ae6-e8ad-11ef-8449-0242ac140006:1-29","time":"2025-02-10T14:28:13-05:00","message":"data import on target for table complete"}
   

   A fetch complete message is written when the fetch task succeeds:

   {"level":"info","type":"summary","fetch_id":"f5cb422f-4bb4-4bbd-b2ae-08c4d00d1e7c","num_tables":3,"tables":["public.employees","public.payments","public.payments"],"skipped_unmigratable_tables":[],"cdc_cursor":"4c658ae6-e8ad-11ef-8449-0242ac140006:1-29","net_duration_ms":6752.847625,"net_duration":"000h 00m 06s","time":"2024-03-18T12:30:37-04:00","message":"fetch complete"}
   

   This message includes a cdc_cursor value. You must set the --defaultGTIDSet replication flag to this value when starting Replicator:

   --defaultGTIDSet 4c658ae6-e8ad-11ef-8449-0242ac140006:1-29
   

Continue MOLT Fetch after an interruption

If MOLT Fetch fails while loading data into CockroachDB from intermediate files, it exits with an error message, fetch ID, and continuation token for each table that failed to load on the target database.

{"level":"info","table":"public.employees","file_name":"shard_01_part_00000001.csv.gz","message":"creating or updating token for duplicate key value violates unique constraint \"employees_pkey\"; Key (id)=(1) already exists."}
{"level":"info","table":"public.employees","continuation_token":"a1b2c3d4-e5f6-7890-abcd-ef1234567890","message":"created continuation token"}
{"level":"info","fetch_id":"f5cb422f-4bb4-4bbd-b2ae-08c4d00d1e7c","message":"continue from this fetch ID"}
{"level":"error","message":"Error: error from fetching table for public.employees: error importing data: duplicate key value violates unique
  constraint \"employees_pkey\" (SQLSTATE 23505)"}

You can use this information to where it was interrupted.

Continuation is only possible under the following conditions:

• All data has been exported from the source database into intermediate files on or .
• The initial load of source data into the target CockroachDB database is incomplete.
• The load uses IMPORT INTO rather than COPY FROM.

Only one fetch ID and set of continuation tokens, each token corresponding to a table, are active at any time. See .

The following command reattempts the data load starting from a specific continuation file, but you can also use individual continuation tokens to .

molt fetch \
--source $SOURCE \
--target $TARGET \
--table-filter 'employees|payments|orders' \
--bucket-path 's3://migration/data/cockroach' \
--table-handling truncate-if-exists \
--ignore-replication-check \
--fetch-id f5cb422f-4bb4-4bbd-b2ae-08c4d00d1e7c \
--continuation-file-name shard_01_part_00000001.csv.gz

Step 4: Verify the initial data load

Use to confirm that the source and target data is consistent. This ensures that the data load was successful.

Run MOLT Verify

1. Run the command, specifying the source and target connection strings and the tables to validate.

   molt verify \
   --source $SOURCE \
   --target $TARGET \
   --table-filter 'employees|payments|orders'
   

2. Check the output to observe verify progress.

   A verification in progress indicates that the task has started:

   {"level":"info","time":"2025-02-10T15:35:04-05:00","message":"verification in progress"}
   

   starting verify messages are written for each specified table:

   {"level":"info","time":"2025-02-10T15:35:04-05:00","message":"starting verify on public.employees, shard 1/1"}
   

   A finished row verification message is written after each table is compared. If num_success equals num_truth_rows and the error counters (num_missing, num_mismatch, num_extraneous, and num_column_mismatch) are all 0, the table verified successfully. Any non-zero values in the error counters indicate data discrepancies that need investigation. For details on each field, refer to the page.

   {"level":"info","type":"summary","table_schema":"public","table_name":"employees","num_truth_rows":200004,"num_success":200004,"num_conditional_success":0,"num_missing":0,"num_mismatch":0,"num_extraneous":0,"num_live_retry":0,"num_column_mismatch":0,"time":"2025-02-10T15:35:05-05:00","message":"finished row verification on public.employees (shard 1/1)"}
   

   A verification complete message is written when the verify task succeeds:

   {"level":"info","net_duration_ms":699.804875,"net_duration":"000h 00m 00s","time":"2025-02-10T15:35:05-05:00","message":"verification complete"}
   

Step 5: Finalize the target schema

Add constraints and indexes

Add any constraints or indexes that you previously removed from the CockroachDB schema to facilitate data load.

If you used the --table-handling drop-on-target-and-recreate option for data load, only and constraints are preserved. You must manually recreate all other constraints and indexes.

For the appropriate SQL syntax, refer to and . Review the on CockroachDB.

Step 6: Begin forward replication

In this step, you will:

• Configure MOLT Replicator with the flags needed for your migration.
• Start MOLT Replicator.
• Understand how to continue replication after an interruption.

Configure MOLT Replicator

When you run replicator, you can configure the following options for replication:

• Replication connection strings: Specify URL-encoded source and target database connections.
• Replicator flags: Specify required and optional flags to configure replicator behavior.
• Replicator metrics: Monitor replication progress and performance.

Replication connection strings

MOLT Replicator uses --sourceConn and --targetConn to specify the source and target database connections.

--sourceConn specifies the connection string of the source database:

--sourceConn 'mysql://{username}:{password}@{protocol}({host}:{port})/{database}'

--targetConn specifies the target CockroachDB connection string:

--targetConn 'postgresql://{username}:{password}@{host}:{port}/{database}'

Follow best practices for securing connection strings. Refer to Secure connections.

Replicator flags

Configure the following flags for continuous replication. For details on all available flags, refer to .

Flag	Description
	Required. Target schema name on CockroachDB where tables will be replicated. Schema name must be fully qualified in the format database.schema.
	Required. Default GTID set for changefeed.
	Required. Staging schema name on CockroachDB for replication metadata and checkpoints. Schema name must be fully qualified in the format database.schema.
	Automatically create the staging schema if it does not exist. Include this flag when starting replication for the first time.
	Explicitly fetch column metadata for MySQL versions that do not support binlog_row_metadata. Requires SELECT permissions on the source database or PROCESS privileges.
	Enable Prometheus metrics at a specified {host}:{port}. Metrics are served at http://{host}:{port}/_/varz.
	Path to a that enables data filtering, routing, or transformations. For examples, refer to .

You can find the starting GTID in the cdc_cursor field of the fetch complete message after the initial data load completes.

Replicator metrics

MOLT Replicator metrics are not enabled by default. Enable Replicator metrics by specifying the flag with a port (or host:port) when you start Replicator. This exposes Replicator metrics at http://{host}:{port}/_/varz. For example, the following flag exposes metrics on port 30005:

--metricsAddr :30005

For guidelines on using and interpreting replication metrics, refer to .

Start MOLT Replicator

With initial load complete, start replication of ongoing changes on the source to CockroachDB using .

MOLT Fetch captures a consistent point-in-time checkpoint at the start of the data load (shown as cdc_cursor in the fetch output). Starting replication from this checkpoint ensures that all changes made during and after the data load are replicated to CockroachDB, preventing data loss or duplication. The following steps use the checkpoint values from the fetch output to start replication at the correct position.

1. Run the replicator command, specifying the GTID from the checkpoint recorded during data load. Use --stagingSchema to specify a unique name for the staging database, and include --stagingCreateSchema to have MOLT Replicator automatically create the staging database. If you filtered tables during the initial load, and specify the path with --userscript.

   replicator mylogical \
   --sourceConn $SOURCE \
   --targetConn $TARGET \
   --targetSchema defaultdb.public \
   --defaultGTIDSet 4c658ae6-e8ad-11ef-8449-0242ac140006:1-29 \
   --stagingSchema defaultdb._replicator \
   --stagingCreateSchema \
   --metricsAddr :30005 \
   --userscript table_filter.ts \
   -v
   
   For MySQL versions that do not support binlog_row_metadata, include --fetchMetadata to explicitly fetch column metadata. This requires additional permissions on the source MySQL database. Grant SELECT permissions with GRANT SELECT ON migration_db.* TO 'migration_user'@'localhost';. If that is insufficient for your deployment, use GRANT PROCESS ON *.* TO 'migration_user'@'localhost';, though this is more permissive and allows seeing processes and server status.

Check that replication is working

1. Verify that Replicator is processing changes successfully. To do so, check the MOLT Replicator logs. Since you enabled debug logging with -v, you should see connection and row processing messages:

   You should see binlog syncer connection and row processing:

   [2025/08/25 15:29:09] [info] binlogsyncer.go:463 begin to sync binlog from GTID set 77263736-7899-11f0-81a5-0242ac120002:1-38
   [2025/08/25 15:29:09] [info] binlogsyncer.go:409 Connected to mysql 8.0.43 server
   INFO   [2025-08-25T15:29:09-05:00] connected to MySQL version 8.0.43
   

   When rows are successfully replicated, you should see debug output like the following:

   DEBUG  [2025-08-25T15:29:38-05:00] upserted rows                                 conflicts=0 duration=1.801ms proposed=1 target="\"molt\".\"public\".\"tbl1\"" upserted=1
   DEBUG  [2025-08-25T15:29:38-05:00] progressed to consistent point: 77263736-7899-11f0-81a5-0242ac120002:1-39
   

   These messages confirm successful replication. You can disable verbose logging after verifying the connection.

Continue MOLT Replicator after an interruption

Run the mylogical command using the same --stagingSchema value from your initial replication command.

Replicator will automatically use the saved GTID (Global Transaction Identifier) from the memo table in the staging schema (in this example, defaultdb._replicator.memo) and track advancing GTID checkpoints there. To have Replicator start from a different GTID instead of resuming from the checkpoint, clear the memo table with DELETE FROM defaultdb._replicator.memo; and run the replicator command with a new --defaultGTIDSet value.

For MySQL versions that do not support binlog_row_metadata, include --fetchMetadata to explicitly fetch column metadata. This requires additional permissions on the source MySQL database. Grant SELECT permissions with GRANT SELECT ON migration_db.* TO 'migration_user'@'localhost';. If that is insufficient for your deployment, use GRANT PROCESS ON *.* TO 'migration_user'@'localhost';, though this is more permissive and allows seeing processes and server status.

replicator mylogical \
--sourceConn $SOURCE \
--targetConn $TARGET \
--targetSchema defaultdb.public \
--stagingSchema defaultdb._replicator \
--metricsAddr :30005 \
--userscript table_filter.ts \
-v

Replication resumes from the last checkpoint without performing a fresh load. Monitor the metrics endpoint at http://localhost:30005/_/varz to track replication progress.

Step 7: Stop application traffic

Once the inital data load has been verified and the target schema has been finalized, it’s time to begin the cutover process. First, stop application traffic to the source. Scale down the Kubernetes cluster to zero pods.

kubectl scale deployment app --replicas=0

Application downtime begins now.

It is strongly recommended that you perform a dry run of this migration in a test environment. This will allow you to practice using the MOLT tools in real time, and it will give you an accurate sense of how long application downtime might last.

Step 8: Stop forward replication

Before you can cut over traffic to the target, the changes to the source database need to finish being written to the target. Once the source is no longer receiving write traffic, MOLT Replicator will take some seconds to finish replicating the final changes. This is known as drainage.

1. Wait for replication to drain, which means that all transactions that occurred on the source database have been fully processed and replicated. There are several ways to determine that replication has fully drained:

   • When replication is caught up, you will not see new upserted rows logs.

   • If you set up the replication metrics endpoint with in the preceding steps, metrics are available at:

     http://{host}:{port}/_/varz
     

     Use the following Prometheus alert expression to observe when the combined rate of upserts and deletes is 0 for each schema:

     sum by (schema) (rate(apply_upserts_total[$__rate_interval]) + rate(apply_deletes_total[$__rate_interval]))
     

   • You can also check Prometheus metrics associated with replication lag, including , , and .

2. Cancel replication by entering ctrl-c to issue a SIGTERM signal. This returns an exit code 0.

Step 9: Verify the replicated data

Repeat Step 4 to verify the updated data.

Step 10: Cut over application traffic

With the target cluster verified and finalized, it’s time to resume application traffic.

Modify application code

In the application back end, make sure that the application now directs traffic to the CockroachDB cluster. For example:

env:
  - name: DATABASE_URL
    value: postgres://root@localhost:26257/defaultdb?sslmode=verify-full

Resume application traffic

Scale up the Kubernetes deployment to the original number of replicas:

kubectl scale deployment app --replicas=3

This ends downtime.

See also