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For a one-time or repeatable MySQL-to-PostgreSQL migration, pgloader can create the target schema, load table data, convert many MySQL types, rebuild keys and indexes, and reset sequences. Start with a disposable PostgreSQL target, run a rehearsal, correct casts and rejected rows, then repeat against the production target. The shortest working command is:
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pgloader mysql://myuser@myhost/dbname pgsql://pguser@pghost/dbnameThe command is only the beginning: views, triggers, stored routines, data-quality exceptions, credentials, and cutover validation require an explicit migration plan.
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What pgloader migrates automatically
pgloader is a command-line migration tool designed to move relational data into PostgreSQL while translating schema definitions and data types. Its MySQL loader can create tables, columns, primary keys, foreign keys, indexes, constraints, comments, and PostgreSQL sequence-backed columns. It also translates MySQL auto_increment columns into PostgreSQL serial-style columns and can represent ON UPDATE CURRENT_TIMESTAMP behavior with a PostgreSQL before-update trigger.
The official tutorial describes pgloader as the tool of choice for moving data from MySQL to PostgreSQL. Treat that as a description of the tool’s purpose, not a guarantee that every application object or value will transfer without review. The MySQL and PostgreSQL references list important unsupported objects, and type conversion depends on the actual schema and data.
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| Migration area | What pgloader can do | What you must verify |
|---|---|---|
| Tables and columns | Create PostgreSQL table definitions and load rows. | Names, schemas, nullability, defaults, and generated values. |
| Keys and indexes | Create primary keys, foreign keys, unique constraints, and indexes. | Constraint success, index names, and application query behavior. |
| Sequences | Reset sequences when requested. | Each sequence is above the current maximum key before writes resume. |
| Comments | Carry table or column comments where supported by the loader. | That comments survived the target schema build. |
| Automatic updates | Translate MySQL ON UPDATE CURRENT_TIMESTAMP behavior to a PostgreSQL before-update trigger. |
The trigger semantics match the application’s expectations. |
| Views, triggers, routines | Not direct, complete migrations for these objects. | Export, rewrite, and test PostgreSQL equivalents separately. |
Prepare both database endpoints
- Create the destination database and login. Create the PostgreSQL database and a user with the privileges needed to create schemas, tables, indexes, constraints, sequences, and data. Limit those privileges to the migration account and target you intend to use.
- Confirm source access. The MySQL account must be able to read the databases and tables selected for migration, including metadata required to inspect columns, keys, and indexes.
- Test network and authentication independently. Verify that the machine running pgloader can reach both database hosts and ports before starting a long load. A MySQL endpoint normally uses port 3306 and a PostgreSQL endpoint normally uses port 5432, but use the actual ports in your environment.
- Protect connection credentials. Connection URLs contain usernames and may contain passwords. Avoid exposing them in shell history, process listings, shared logs, or an accidentally committed load file. Use an appropriate secret-management or operating-system protection method for your environment.
- Choose a disposable rehearsal target. The first run should not be pointed at a production PostgreSQL database. Restore or create an isolated target where tables can be dropped, recreated, and inspected without affecting application traffic.
A connection URL follows the form mysql://user:password@host:3306/dbname for MySQL and pgsql://user:password@host:5432/dbname for PostgreSQL. pgloader’s MySQL documentation also describes a JDBC form; use that documented form when the normal URL cannot represent your connection details. Encode credentials appropriately for the URL syntax and do not paste secrets into tickets or public logs.
Run the simplest migration first
For a small rehearsal with ordinary table definitions, run:
pgloader mysql://myuser@myhost/dbname pgsql://pguser@pghost/dbnameThis lets pgloader inspect the MySQL schema, create corresponding PostgreSQL objects, load rows, and report warnings or rejected data. Add the password only when your environment protects the command line, or use the credential mechanism appropriate to your deployment.
Do not assume that a successful process exit proves semantic correctness. Save the console output, inspect warnings and rejected rows, and compare the resulting schema and data with the source. If the rehearsal exposes a type mismatch, zero date, encoding problem, or constraint failure, fix the load rules or source data before repeating the load.
Move production work into a load file
A version-controlled .load file makes the migration repeatable. It records source and destination, creation options, memory settings, search path, casts, view handling, and pre-load SQL in one reviewable artifact. The following pattern follows the structure of the official tutorial; replace every endpoint, schema, memory value, and object list with values appropriate to your database:
LOAD DATABASE
FROM mysql://root@localhost/sakila
INTO postgresql:///sakila
WITH include drop, create tables, no truncate,
create indexes, reset sequences, foreign keys
SET maintenance_work_mem to '128MB',
work_mem to '12MB',
search_path to 'sakila'
CAST type datetime to timestamptz
drop default drop not null using zero-dates-to-null,
type date drop not null drop default using zero-dates-to-null
MATERIALIZE VIEWS film_list, staff_list
BEFORE LOAD DO
$$ create schema if not exists sakila; $$;The sample is intentionally explicit. It is not a universal production configuration: credentials, schema names, memory settings, casts, and materialized views must reflect the actual source and target.
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| Clause | Purpose | Operational caution |
|---|---|---|
include drop |
Allows pgloader to drop target tables whose names appear in the source before recreating them. | Destructive. Use only on an intentionally disposable or tightly controlled target. |
create tables |
Creates destination table definitions. | Check the generated schema after the load. |
no truncate |
Leaves the load from silently truncating existing target tables under this option set. | Decide deliberately whether the target is empty and how repeat runs should behave. |
create indexes |
Builds indexes described by the source. | Validate names, uniqueness, and query performance after loading. |
reset sequences |
Moves sequence values in line with loaded key values. | Confirm every sequence is greater than the current maximum key. |
foreign keys |
Creates foreign-key relationships. | Rejected rows or inconsistent source data can prevent constraints from being created or validated. |
SET |
Adjusts PostgreSQL memory settings and the target search_path for the load. |
Use values your PostgreSQL instance permits; the sample values are not a benchmark or universal recommendation. |
BEFORE LOAD DO |
Runs SQL before loading, such as creating a destination schema. | Review the SQL for the selected target and permissions. |
Limit tables and rename objects deliberately
Large databases often need a staged migration. pgloader can scope a load with INCLUDING ONLY TABLE NAMES MATCHING and EXCLUDING TABLE NAMES MATCHING. Use inclusion rules when only a known set belongs in the target; use exclusions for tables that are temporary, archived, or handled by another process. Keep the filter in the load file and include filtered tables in your validation checklist so an omitted table is not mistaken for a failed transfer.
When source metadata has incorrect encoding information, DECODING TABLE NAMES MATCHING ... AS ... can tell pgloader how to interpret matching table names. ALTER TABLE NAMES MATCHING can rename tables, move them to another schema, or apply table settings in pgloader’s in-memory representation. These transformations affect the target naming model, so document the old and new names for application code, grants, and post-load checks.
Control MySQL-to-PostgreSQL type conversion
User-defined CAST rules are evaluated before pgloader’s built-in defaults, and the first matching rule wins. A rule may match a MySQL type or a qualified column. Guards can distinguish unsigned values, defaults, type modifiers, auto_increment, and on_update_current_timestamp. Put the most specific rule first, then rehearse and inspect the resulting PostgreSQL type.
Zero dates and invalid date values
MySQL systems sometimes contain zero dates such as 0000-00-00, which PostgreSQL cannot represent as an ordinary date. The sample load file uses using zero-dates-to-null and drops the original default and NOT NULL requirement for affected date and datetime columns. That is a data-policy decision: converting a sentinel to NULL changes how the application distinguishes “unknown” from a real date. Confirm that every consuming query and validation rule accepts the new value.
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The sample maps MySQL datetime to PostgreSQL timestamptz. Choose that only when the source value should represent an instant with time-zone normalization. If the application treats the value as a wall-clock timestamp without a zone, a different PostgreSQL type or transformation may be appropriate. Check representative values around daylight-saving transitions and compare application-generated timestamps after the rehearsal.
Boolean-like integers
MySQL TINYINT(1) is frequently used as a boolean, but the type declaration alone does not prove that every stored value is 0 or 1. A custom cast can map a known boolean column to PostgreSQL boolean; first inspect the data for unexpected integers and decide how those values should be handled. If the column is genuinely numeric, preserve a numeric PostgreSQL type instead.
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Unsigned numbers
PostgreSQL integer types do not have MySQL’s unsigned modifier. Check the observed and possible range of every unsigned column before choosing a signed PostgreSQL integer or a wider numeric type. A cast that works for current rows can still overflow when a future value exceeds the signed range.
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Enum-like MySQL columns require a choice between PostgreSQL enum types, constrained text, or unconstrained text. Make that choice based on how the application adds values and validates input, then test invalid and newly added values. Inspect binary columns separately and confirm whether they should become PostgreSQL binary data or decoded text. If source character-set metadata is wrong, use the decoding rules available for the affected table names and verify non-ASCII samples rather than relying on row counts alone.
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pgloader converts MySQL auto_increment columns to PostgreSQL serial-style columns and can reset their sequences. Verify that the sequence is above the maximum imported key before allowing inserts. For columns using ON UPDATE CURRENT_TIMESTAMP, inspect the generated before-update trigger and compare its behavior with the original application logic; a mechanically translated trigger may not cover every business rule that previously ran in application code.
Objects pgloader does not migrate directly
The MySQL reference lists views and triggers as unsupported for direct migration, and its coverage of geometric types is limited to POINT. The PostgreSQL reference also identifies views, triggers, stored procedures, and functions as outside the direct migration path. Plan these objects as a separate conversion stream:
- Export definitions and dependencies from MySQL before the cutover.
- Rewrite syntax and data-type assumptions for PostgreSQL rather than copying SQL verbatim.
- Create the PostgreSQL versions after the base tables and required data exist, unless a dependency requires an earlier stub.
- Test each view, trigger, procedure, and function with representative reads and writes, including error paths and transaction behavior.
- Remove temporary compatibility objects only after application tests pass.
If a view is useful during the load, MATERIALIZE VIEWS can create a materialized representation for named views in the load process. That does not recreate the original live view semantics; decide how and when the PostgreSQL view or refresh process will be implemented.
Rehearse, inspect, and validate the target
Use a disposable target for a complete rehearsal. A rehearsal is more useful than a syntactic check because it reveals actual values that trigger casts, constraints, encoding errors, and rejected rows.
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- Row counts: Compare every source and target table, including tables selected or omitted by inclusion and exclusion filters. Explain intentional differences such as filtered data or rows rejected for invalid values.
- Keys and constraints: Check primary keys, foreign keys, unique constraints, nullability, and default expressions. Confirm that constraints represent the source rules and that no invalid source rows were silently excluded.
- Indexes: Compare index columns, uniqueness, and names. Verify that the application queries use the intended target indexes.
- Sequences: For every serial-style key, compare the sequence value with the maximum imported key and perform a controlled insert in the rehearsal environment.
- Converted values: Inspect integers, unsigned values, enum-like columns, dates, timestamps, zero dates, binary data, and text containing non-ASCII characters.
- Behavior: Compare representative aggregates and application queries against both databases. Include joins that exercise foreign keys and updates that exercise timestamp behavior.
- Unsupported objects: Create and test rewritten views, triggers, stored procedures, and functions separately.
- Artifacts: Retain the load file, pgloader warnings, rejected-row details, target logs, and schema-diff results as part of the migration record.
Repeat the rehearsal after each change to a cast, filter, schema rule, or source cleanup. Only start a final load when the differences are understood and accepted.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Troubleshoot common failures
The connection fails before loading
Check hostname, port, database name, credentials, firewall rules, TLS requirements, and source or target privileges from the machine running pgloader. Test each endpoint separately, then retry the two-ended command. A correct URL cannot overcome a blocked route or a user that lacks metadata or DDL permissions.
Rows are rejected because of a type or constraint
Read the rejected-row details and identify the first failing column or constraint. Add a targeted cast, clean the source value, widen the PostgreSQL type where the range requires it, or defer a constraint only when the final data model remains safe. Re-run the rehearsal and verify that the fix did not change unrelated columns.
Dates become null
That result is expected when zero-dates-to-null handles MySQL zero dates. Confirm that the affected columns were intended to use the conversion and that application code treats NULL correctly. If zero dates carry a different business meaning, use a documented alternative transformation instead of accepting the default conversion.
The target already contains tables
Review whether include drop, truncation behavior, or an existing schema is responsible. Never enable a destructive option against a target containing data you need. Point the rehearsal at a clean database or use explicit table and schema rules so the operation’s scope is unambiguous.
Names or characters are corrupted
Check source encoding metadata and target encoding assumptions. Apply a decoding rule for affected table names when metadata is wrong, then inspect actual multilingual names and text values. A successful load count does not prove that bytes were interpreted correctly.
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Plan cutover and repeatability
A pgloader run is easiest to reason about when the source is stable. Decide how the application will stop writes, how long the final load may take, and how you will verify the target before redirecting traffic. The canonical documentation provides no universal runtime or throughput figure: duration depends on database size, schema, indexes, network, and target configuration. Measure your own rehearsal instead of promising a fixed window.
Keep the final .load file under version control, along with the source and target schema descriptions, cast rationale, filter list, validation results, and rewritten-object tests. If the migration must be repeated, start from a known target state and make destructive clauses explicit. Do not treat an undocumented manual edit made during an emergency run as the new process.
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Direct loading is not the only option. Compare approaches against the characteristics of your database and cutover plan rather than against an assumed speed advantage.
| Decision axis | Direct pgloader load | Dump and restore or scripted conversion | Managed migration service |
|---|---|---|---|
| Schema and type conversion | Built-in MySQL-to-PostgreSQL translation plus explicit casts. | Depends on dump format and the conversion scripts you maintain. | Depends on the service’s supported engines and conversion rules. |
| Views, triggers, and stored routines | Require separate export and PostgreSQL rewrite. | Usually require separate rewrite and dependency handling. | May offer conversion assistance, but support must be checked for the exact object types. |
| Repeatability and filtering | Load files provide versioned options, table filters, renames, and casts. | Scripts can be repeatable but require you to maintain every transformation. | Often configured through a service workflow; export the configuration and rules for auditability. |
| Downtime and cutover | Plan a stable source or a final write freeze; pgloader itself does not define your application’s cutover. | Same operational decision, with additional dump and restore stages. | Some services provide replication or change capture; verify the specific offering rather than assuming it. |
| Security and network path | Credentials and connectivity are under your control on the host running pgloader. | Security depends on where dumps are stored and executed. | Requires trust and network configuration for the provider handling the migration. |
| Observability and retry behavior | Use pgloader output, rejected rows, target logs, and your own validation artifacts. | Use dump, restore, and script logs. | Use the provider’s monitoring and retry model, while retaining independent validation. |
| Scale and throughput | Depends on schema, data volume, network, indexes, and PostgreSQL configuration; no universal figure is established. | Depends on dump format, storage, and restore tuning. | Depends on service limits, region, instance size, and network path. |
| Manual PostgreSQL work | Still required for unsupported objects and application-specific semantics. | Often substantial when translating types and behavior. | Varies by engine pair and conversion coverage. |
pgloader is a strong fit when you want an inspectable command or load file, automatic baseline schema conversion, explicit casts, and control over where credentials and data are processed. Choose another method when its replication, compliance, object-conversion, or operational requirements better match your cutover.
Bottom line
Use pgloader in two passes: first as a controlled rehearsal that exposes type and data-quality problems, then as a repeatable final load from a reviewed .load file. The tool can handle much of the table, key, index, comment, sequence, and common type work, but it does not eliminate PostgreSQL design decisions. Explicitly map zero dates, unsigned and boolean-like values, timestamps, encodings, and auto-increment keys; rewrite views, triggers, procedures, and functions; and validate every table, constraint, sequence, representative query, and rejected row before cutover.
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