Delta Migration from PostgreSQL

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.
OID LOB types in PostgreSQL are not supported, although similar types like BYTEA are 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 .

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.

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 WITH PASSWORD 'password';

Grant the user privileges to connect, view schema objects, and select the tables you migrate.

GRANT CONNECT ON DATABASE migration_db TO migration_user;
GRANT USAGE ON SCHEMA migration_schema TO migration_user;
GRANT SELECT ON ALL TABLES IN SCHEMA migration_schema TO migration_user;
ALTER DEFAULT PRIVILEGES IN SCHEMA migration_schema GRANT SELECT ON TABLES TO migration_user;

Grant the SUPERUSER role to the user (recommended for replication configuration):

ALTER USER migration_user WITH SUPERUSER;

Alternatively, grant the following permissions to create replication slots, access replication data, create publications, and add tables to publications:

ALTER USER migration_user WITH LOGIN REPLICATION;
GRANT CREATE ON DATABASE migration_db TO migration_user;
ALTER TABLE migration_schema.table_name OWNER TO migration_user;

Run the ALTER TABLE command for each table to replicate.

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.

Verify that you are connected to the primary server:

SELECT pg_is_in_recovery();

You should get a false result:

 pg_is_in_recovery
-------------------
 f

Enable logical replication by setting wal_level to logical in postgresql.conf or in the SQL shell. For example:

ALTER SYSTEM SET wal_level = 'logical';

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. For example, a PostgreSQL source table defined as CREATE TABLE migration_schema.tbl (pk INT PRIMARY KEY); must have a corresponding schema and table in CockroachDB:
CREATE SCHEMA migration_schema; CREATE TABLE migration_schema.tbl (pk 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 .

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

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

Grant the same privileges for internal MOLT tables in the public CockroachDB 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 migration_schema 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.

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. You must include --pglogical-replication-slot-name and --pglogical-publication-and-slot-drop-and-recreate to automatically create the publication and replication slot during the data load.
molt fetch \ --source $SOURCE \ --target $TARGET \ --schema-filter 'migration_schema' \ --table-filter 'employees|payments|orders' \ --bucket-path 's3://migration/data/cockroach' \ --table-handling truncate-if-exists \ --pglogical-replication-slot-name molt_slot \ --pglogical-publication-and-slot-drop-and-recreate

Check the output to observe fetch progress. If you included the --pglogical-replication-slot-name and --pglogical-publication-and-slot-drop-and-recreate flags, a publication named molt_fetch is automatically created:

{"level":"info","time":"2025-02-10T14:28:11-05:00","message":"dropping and recreating publication molt_fetch"}

A starting fetch message indicates that the task has started:

{"level":"info","type":"summary","num_tables":3,"cdc_cursor":"0/43A1960","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":"migration_schema.employees","time":"2025-02-10T14:28:11-05:00","message":"data extraction phase starting"}

{"level":"info","table":"migration_schema.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":"migration_schema.employees","time":"2025-02-10T14:28:12-05:00","message":"starting data import on target"}

{"level":"info","table":"migration_schema.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":"0/43A1960","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":["migration_schema.employees","migration_schema.payments","migration_schema.payments"],"skipped_unmigratable_tables":[],"cdc_cursor":"0/3F41E40","net_duration_ms":6752.847625,"net_duration":"000h 00m 06s","time":"2024-03-18T12:30:37-04:00","message":"fetch complete"}

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 \
--schema-filter 'migration_schema' \
--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

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'

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.
Tuning parameters: Optimize replication performance and resource usage.
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 'postgresql://{username}:{password}@{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. PostgreSQL replication slot name. Must match the slot name specified with `--pglogical-replication-slot-name` in the MOLT Fetch command.
	Required. PostgreSQL publication name. Must match the publication name created either manually or automatically with `--pglogical-publication-and-slot-drop-and-recreate` in the MOLT Fetch command.
	Required. Target schema name on CockroachDB where tables will be replicated. Schema name must be fully qualified in the format `database.schema`.
	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.
	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 .

Tuning parameters

Configure the following to optimize replication throughput and resource usage. Test different combinations in a pre-production environment to find the optimal balance of stability and performance for your workload.

The following parameters apply to PostgreSQL, Oracle, and CockroachDB (failback) sources.

Flag	Description
	Control the maximum number of concurrent target transactions. Higher values increase throughput but require more target connections. Start with a conservative value and increase based on target database capacity.
	Balance throughput and latency. Controls how many mutations are batched into each query to the target. Increase for higher throughput at the cost of higher latency.
	Control memory usage during operation. Increase to allow higher throughput at the expense of memory; decrease to apply backpressure and limit memory consumption.
	Set larger than by a safety factor to avoid exhausting target pool connections. Replicator enforces setting parallelism to 80% of this value.
	Reduce the number of queries to the target by combining multiple mutations on the same primary key within each batch. Disable only if exact mutation order matters more than end state.
	Improve apply throughput for independent tables and table groups that share foreign key dependencies. Increases memory and target connection usage, so ensure you increase or reduce .
	Set to the maximum allowable time between flushes (for example, `10s` if data must be applied within 10 seconds). Works with to control when buffered mutations are committed to the target.
	Lower this value if constraint violations resolve quickly on your workload to make retries more frequent and reduce latency. Do not lower if constraint violations take time to resolve.
	Applies to (`replicator start`) scenarios only. Balance memory usage and throughput. Increase to read more rows at once from the CockroachDB staging cluster for higher throughput, at the cost of memory pressure. Decrease to reduce memory pressure and increase stability.

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.

Run the replicator command, using the same slot name that you specified with --pglogical-replication-slot-name and the publication name created by --pglogical-publication-and-slot-drop-and-recreate in the Fetch command. Use --stagingSchema to specify a unique name for the staging database, and include --stagingCreateSchema to have MOLT Replicator automatically create the staging database:
replicator pglogical \ --sourceConn $SOURCE \ --targetConn $TARGET \ --targetSchema defaultdb.migration_schema \ --slotName molt_slot \ --publicationName molt_fetch \ --stagingSchema defaultdb._replicator \ --stagingCreateSchema \ --metricsAddr :30005 \ -v

Check that replication is working

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 periodic primary keepalive messages:

DEBUG  [2025-08-25T14:38:10-05:00] primary keepalive received                    ReplyRequested=false ServerTime="2025-08-25 14:38:09.556773 -0500 CDT" ServerWALEnd=0/49913A58
DEBUG  [2025-08-25T14:38:15-05:00] primary keepalive received                    ReplyRequested=false ServerTime="2025-08-25 14:38:14.556836 -0500 CDT" ServerWALEnd=0/49913E60

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

DEBUG  [2025-08-25T14:40:02-05:00] upserted rows                                 conflicts=0 duration=7.855333ms proposed=1 target="\"molt\".\"public\".\"tbl1\"" upserted=1
DEBUG  [2025-08-25T14:40:02-05:00] progressed to LSN: 0/49915DD0

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

Continue MOLT Replicator after an interruption

Run the pglogical command using the same --stagingSchema value from your initial replication command. Be sure to specify the same --slotName value that you used during your initial replication command. The replication slot on the source PostgreSQL database automatically tracks the LSN (Log Sequence Number) checkpoint, so replication will resume from where it left off.

replicator pglogical \
--sourceConn $SOURCE \
--targetConn $TARGET \
--targetSchema defaultdb.migration_schema \
--slotName molt_slot \
--stagingSchema defaultdb._replicator \
--metricsAddr :30005 \
-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.

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 .
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.

​Example scenario

​Before the migration

​Limitations

​MOLT Fetch limitations

​MOLT Replicator limitations

​MOLT Verify limitations

​Step 1: Prepare the source database

​Create migration user on source database

​Configure source database for replication

​Step 2: Prepare the target database

​Define the target tables

​Schema Conversion Tool

​Drop constraints and indexes

​Create the SQL user

​IMPORT INTO privileges

​COPY FROM privileges

​Set session variable

​Replication privileges

​Configure GC TTL

​Step 3: Load data into CockroachDB

​Configure MOLT Fetch

​Run MOLT Fetch

​Continue MOLT Fetch after an interruption

​Step 4: Verify the initial data load

​Run MOLT Verify

​Step 5: Finalize the target schema

​Add constraints and indexes

​Step 6: Begin forward replication

​Configure MOLT Replicator

​Replication connection strings

​Replicator flags

​Tuning parameters

​Replicator metrics

​Start MOLT Replicator

​Check that replication is working

​Continue MOLT Replicator after an interruption

​Step 7: Stop application traffic

​Step 8: Stop forward replication

​Step 9: Verify the replicated data

​Step 10: Cut over application traffic

​Modify application code

​Resume application traffic

​See also

Example scenario

Before the migration

Limitations

MOLT Fetch limitations

MOLT Replicator limitations

MOLT Verify limitations

Step 1: Prepare the source database

Create migration user on source database

Configure source database for replication

Step 2: Prepare the target database

Define the target tables

Schema Conversion Tool

Drop constraints and indexes

Create the SQL user

`IMPORT INTO` privileges

`COPY FROM` privileges

Set session variable

Replication privileges

Configure GC TTL

Step 3: Load data into CockroachDB

Configure MOLT Fetch

Run MOLT Fetch

Continue MOLT Fetch after an interruption

Step 4: Verify the initial data load

Run MOLT Verify

Step 5: Finalize the target schema

Add constraints and indexes

Step 6: Begin forward replication

Configure MOLT Replicator

Replication connection strings

Replicator flags

Tuning parameters

Replicator metrics

Start MOLT Replicator

Check that replication is working

Continue MOLT Replicator after an interruption

Step 7: Stop application traffic

Step 8: Stop forward replication

Step 9: Verify the replicated data

Step 10: Cut over application traffic

Modify application code

Resume application traffic

See also