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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorspgloader is the fastest practical starting point for moving a MySQL database into PostgreSQL when you need schema conversion, data loading, and common type mappings in one repeatable process. A simple migration can be one command, but a production cutover should use a version-controlled load file, a disposable rehearsal database, explicit cast rules, and a validation checklist. Views, triggers, stored procedures, and functions require separate export or rewriting because pgloader does not migrate them directly.
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What pgloader does—and what it does not do
pgloader connects to a source database, creates PostgreSQL tables, transfers rows in parallel, and applies conversion rules while loading. Its MySQL workflow can translate table definitions, constraints, indexes, primary keys, foreign keys, comments, and MySQL auto_increment columns into PostgreSQL equivalents. It can also translate MySQL ON UPDATE CURRENT_TIMESTAMP behavior into a PostgreSQL BEFORE UPDATE trigger.
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Those automatic conversions are a starting point, not proof that the target behaves exactly like the application expects. You still need to inspect generated DDL, check data types and defaults, and test application queries.
Direct migration has important limits. The MySQL and PostgreSQL references list views, triggers, stored procedures, and functions as unsupported for direct migration. Only the MySQL POINT geometric type is covered. Export unsupported objects separately, rewrite them in PostgreSQL syntax, and test them after the data load.
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Plan the migration before running pgloader
Inventory the source
- Record every database, table, column type, index, constraint, view, trigger, routine, event, and scheduled job that matters to the application.
- Identify MySQL-specific behavior such as zero dates, unsigned integers,
TINYINT(1)booleans,ENUMvalues, implicit character-set conversions, andON UPDATEtimestamp clauses. - Measure table sizes and estimate the network path between MySQL and PostgreSQL. There is no authoritative universal runtime or throughput figure; performance varies with row count, indexes, network capacity, and target configuration.
- Decide whether the application will be stopped for a final load or whether you need a replication or dual-write cutover design outside pgloader.
Create a protected PostgreSQL target
Create the target database and a migration user with the privileges needed to create schemas, tables, indexes, constraints, sequences, and triggers. Grant only the permissions required for the migration, and remove or reduce them after cutover. Keep credentials out of shell history, source control, and shared logs. Prefer a secret manager or a protected environment variable when your operating environment supports one.
Test both connections
Use a MySQL URL such as mysql://user:password@host:3306/dbname and a PostgreSQL URL such as pgsql://user:password@host:5432/dbname. The MySQL reference also documents a JDBC connection form; use that form when your MySQL deployment or driver setup requires it. Verify DNS, firewall rules, TLS requirements, authentication, and the target user’s DDL privileges before starting a full load.
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For a first rehearsal, use a disposable PostgreSQL database and the shortest command:
pgloader mysql://myuser@myhost/dbname pgsql://pguser@pghost/dbnameThe credentials in this example are intentionally omitted from the URLs. Supplying a password interactively or through a protected mechanism is safer than putting a reusable password directly in a process list or committed file.
This command asks pgloader to create the target schema and load the source data using its default MySQL conversion rules. Capture the complete terminal output. Warnings, rejected rows, and target-server errors are migration findings, not harmless noise.
When the one-line command is enough
A direct command is reasonable for a small, uncomplicated database when you can recreate the target and the source uses conventional types. It is useful for discovering conversion problems quickly.
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When to stop using a one-line command
Use a load file as soon as you need casts, table filtering, renames, schema changes, memory settings, materialized views, or a repeatable production procedure. A load file makes every option reviewable and lets you repeat the same migration after correcting data-quality problems.
Build a repeatable .load file
Store the following pattern in version control after replacing the credentials, database names, schema, casts, and resource settings with values for your environment:
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
$$ create schema if not exists sakila; $$;Run a file with the pgloader command appropriate to your installation, for example:
pgloader migration.loadThe sample uses the Sakila names from the official tutorial structure. Treat it as a pattern, not a drop-in production configuration.
Understand the major options
| Option | Effect | Operational caution |
|---|---|---|
create tables |
Creates target table definitions. | Review generated types, defaults, and nullability before cutover. |
create indexes |
Builds indexes described by the source. | Index creation consumes target I/O and can extend the load window. |
foreign keys |
Creates foreign-key constraints. | Bad or orphaned source data can cause constraint failures. |
reset sequences |
Moves generated sequences beyond the current key values. | Verify the next generated value is greater than every existing key. |
no truncate |
Does not truncate target tables before loading. | Do not use a nonempty target unless you deliberately understand duplicate and merge behavior. |
include drop |
Allows pgloader to drop target tables whose names occur in the source. | Destructive: use only on an intentionally disposable or tightly controlled target. |
search_path |
Sets the PostgreSQL schema used by unqualified objects. | Ensure the schema exists and that the migration user can use it. |
Memory settings such as maintenance_work_mem and work_mem affect the target session. Increase them only within the memory budget of the PostgreSQL server; the sample values are not universal recommendations.
Control which tables and schemas move
Large systems often need a staged migration rather than an all-or-nothing copy. Use INCLUDING ONLY TABLE NAMES MATCHING to select an allow-list and EXCLUDING TABLE NAMES MATCHING to omit tables that are temporary, archival, or regenerated by the application. Keep the filtering expressions in the load file so a rehearsal and the final run select the same objects.
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If source encoding metadata is incorrect, DECODING TABLE NAMES MATCHING ... AS ... lets you tell pgloader how to decode 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 before creation.
Filtering changes the validation obligation: compare row counts for every table that was included, and document every excluded table and the reason it is absent.
Map MySQL types deliberately
How pgloader chooses a cast
User-defined CAST rules are evaluated before built-in defaults, and the first matching rule wins. A rule can match a MySQL type or a qualified column. Guards can distinguish unsigned values, defaults, typemods, auto_increment, and on_update_current_timestamp. Order specific rules before broad ones so an early match does not hide a later exception.
Common conversion decisions
| MySQL case | Why it needs review | Typical action |
|---|---|---|
TINYINT(1) |
Many applications use it as a boolean, but it is still an integer in MySQL. | Cast to PostgreSQL boolean only when the stored values and application semantics are strictly true/false. |
| Unsigned integers | PostgreSQL integer ranges are signed; large unsigned values can overflow a signed target type. | Select a wider PostgreSQL numeric type or clean values before loading, then test boundary values. |
ENUM |
MySQL’s enum implementation and invalid-value behavior do not map transparently to every PostgreSQL design. | Choose text with a check constraint, a PostgreSQL enum, or a lookup table according to how the application evolves values. |
| Binary columns | Binary bytes must not be interpreted as text in the target encoding. | Use a binary-compatible target type and verify round trips with representative byte sequences. |
DATETIME and TIMESTAMP |
Timezone semantics differ, and an apparently identical timestamp can represent a different instant. | Choose timestamp or timestamptz intentionally and test values around timezone transitions. |
| Zero dates | Values such as 0000-00-00 are accepted by some MySQL configurations but are not valid PostgreSQL dates. |
Use zero-dates-to-null where null is semantically correct, or cleanse and map them to a documented sentinel before loading. |
The sample load file converts datetime to timestamptz and applies zero-dates-to-null to date-like values while dropping their default and not-null properties. That is appropriate only when a missing date is acceptable. If the application requires a value, clean the source or choose a different mapping instead of silently introducing nulls.
Preserve generated keys safely
pgloader documents conversion of MySQL auto_increment columns to PostgreSQL serial-style columns. After loading, inspect the generated sequence and run a test insert in a transaction. The sequence must be above the current maximum key; otherwise the first application insert can fail with a duplicate-key error. The reset sequences option helps, but it does not replace verification.
Handle automatic update timestamps
MySQL’s ON UPDATE CURRENT_TIMESTAMP behavior is translated to a PostgreSQL before-update trigger. Confirm that the trigger fires on the same updates as before, that explicit timestamp assignments retain the intended meaning, and that your application’s auditing code does not now update a column twice.
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Rehearse, inspect, and correct
- Clone the target environment. Create an empty PostgreSQL database that is disposable and sized close enough to expose permission, encoding, and resource problems.
- Run the load file. Keep the output, PostgreSQL server log, and rejected-row details together with the exact file revision used.
- Inspect the generated schema. Check every table’s columns, defaults, nullability, primary key, foreign keys, unique constraints, indexes, sequences, and schema placement.
- Investigate every warning. Classify it as an expected conversion, a rejected row, a truncation risk, an encoding issue, or an actual failure. Do not proceed merely because the process returned control to the shell.
- Fix casts or source data. Update the load file or cleanse the MySQL data, then destroy and recreate the rehearsal target so the next run is from a known state.
- Repeat until the result is deterministic. A second run should produce the same schema and row totals when the source has not changed.
Do not run include drop against a production database unless dropping matching target tables is an explicitly approved part of the cutover. A separate disposable rehearsal is the safest place to test destructive options.
What to do with views, triggers, and stored routines
Because pgloader does not directly migrate MySQL views, triggers, stored procedures, or functions, treat them as a separate workstream:
- Export definitions from MySQL before the migration and place them under version control.
- Rewrite MySQL syntax, delimiter handling, procedural language, date functions, error handling, and identifier quoting for PostgreSQL.
- Recreate views after base tables and data are present. If a view is expensive and read-only, consider whether a materialized view is appropriate; the load-file
MATERIALIZE VIEWSclause is an explicit choice, not a guarantee that every source view will work unchanged. - Reimplement triggers and verify firing order, transition values, recursion behavior, and transaction effects.
- Replace stored procedures and functions with tested PostgreSQL routines or move the logic into the application where that is the safer design.
- Run application-level tests for every path that depends on these objects.
Do not assume that a successful table load means the application is feature-complete. Unsupported objects are often the difference between a data copy and a usable migration.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Validate the PostgreSQL result
Validation should be a written checklist, not an informal spot check. Complete these checks before switching application traffic:
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- Keys and constraints: verify primary keys, foreign keys, unique constraints, indexes, and nullability. Check for orphaned foreign keys if constraints were deferred or omitted.
- Sequences: confirm every sequence or identity value is greater than the current maximum key, then perform a rolled-back insert test.
- Types and ranges: inspect converted integers, unsigned values, enum-like columns, dates, timestamps, binary data, and text encodings. Include maximum and minimum source values in test cases.
- Aggregates: compare representative sums, counts, minimums, maximums, and grouped totals. Aggregates can reveal truncation or timezone errors that row counts miss.
- Queries: execute representative application queries against both databases and compare result sets, ordering assumptions, null handling, and pagination.
- Unsupported objects: recreate and test views, triggers, stored procedures, and functions separately.
- Logs and artifacts: retain pgloader warnings, rejected rows, PostgreSQL logs, the load file, and schema-diff results so the migration can be audited or repeated.
Cutover and rollback planning
Freeze or quiesce writes long enough to produce a consistent final source snapshot, unless you have designed a separate change-capture or dual-write process. Run the corrected load against the final target, perform the validation checklist, deploy the PostgreSQL-compatible application configuration, and monitor errors, latency, constraint violations, and sequence allocation.
Keep the MySQL database available and unchanged for the agreed rollback window. Define in advance which writes must be replayed or discarded if you revert; simply pointing the application back at MySQL after new PostgreSQL writes have occurred can lose data.
Choosing pgloader versus other migration approaches
pgloader is attractive when you want an open, scriptable conversion with explicit casts and table filtering. A dump-and-restore workflow may offer more control over a full logical backup but usually requires you to perform MySQL-to-PostgreSQL schema and type rewrites yourself. A managed migration service may provide monitoring, retries, and change replication, but introduces provider-specific configuration, network requirements, and cost.
| Decision axis | Questions to ask |
|---|---|
| Schema and type conversion | Does the approach handle your unsigned values, zero dates, enums, timestamps, binary columns, and generated keys? |
| Views and routines | Will you rewrite unsupported objects manually, or does the service offer a compatible conversion path? |
| Repeatability and filtering | Can you store table selection, casts, renames, and resource settings in version control? |
| Downtime and cutover | Can the method provide a consistent final snapshot or change capture within your outage budget? |
| Security | How are credentials protected, and which hosts, ports, TLS settings, and privileges are required? |
| Observability and retries | Can you identify rejected rows, resume or repeat safely, and retain logs? |
| Scale and throughput | What are the measured results for your data size, indexes, network, and target hardware? Do not rely on a universal benchmark. |
| Manual PostgreSQL work | How much application SQL, routine code, and operational behavior must change after the data copy? |
For many teams, the practical answer is hybrid: use pgloader for the repeatable base-table transfer and handle unsupported objects, cutover coordination, and application changes as separately tested deliverables.
Troubleshooting common failures
Authentication or connection errors
Confirm the hostname resolves from the pgloader machine, the port is reachable, the server allows that client address, and the credentials are valid. Check whether TLS is mandatory and whether the PostgreSQL role has permission to create the requested schema and objects.
Invalid date or timestamp errors
Find the offending source values, especially zero dates and timezone-sensitive timestamps. Apply a narrowly scoped cast using zero-dates-to-null only when null is correct, or cleanse the source and rerun the rehearsal.
Numeric overflow
Compare the source column’s unsigned range with the selected PostgreSQL type. Widen the destination type or reject and remediate out-of-range data before loading; do not assume a signed integer is equivalent to an unsigned MySQL column.
Duplicate keys after loading
Check whether the target was nonempty, whether the source contains duplicate values that MySQL tolerated under a different collation or constraint set, and whether a sequence was reset. Recreate the target for a clean rehearsal and inspect constraints before retrying.
Encoding or garbled text
Verify the source connection character set, table metadata, and target encoding. Use the documented table-name decoding option when identifiers—not data—are encoded incorrectly, and test representative multilingual text after loading.
Application behavior changed
Compare collation and case-sensitivity assumptions, null behavior, timestamp zones, auto-generated keys, and SQL syntax. PostgreSQL is not a drop-in MySQL SQL dialect; migrate application queries and routines as part of the cutover plan.
A concise production checklist
- Target database and least-privilege migration role created.
- Both endpoints reachable with protected credentials.
- Source inventory completed, including unsupported objects.
- Version-controlled load file reviewed.
- Table filters, renames, schemas, casts, and memory settings documented.
- Disposable rehearsal completed with warnings and rejected rows resolved.
- Views, triggers, procedures, and functions rewritten and tested.
- Final consistency and cutover window approved.
- Row counts, constraints, indexes, sequences, types, aggregates, and application queries validated.
- Rollback conditions, retained MySQL access, and migration artifacts agreed.
Bottom line
Start with pgloader’s one-line command to expose compatibility problems, then move to a version-controlled load file for every serious migration. Explicitly map zero dates, timestamps, unsigned values, booleans, enums, binary data, and generated keys; rehearse on a disposable target; and validate more than row counts. pgloader can move the relational foundation efficiently, but PostgreSQL rewrites for unsupported views, triggers, stored routines, and application SQL remain your responsibility.
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