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To migrate an application from SQLite to PostgreSQL safely, prepare the PostgreSQL schema, transfer the existing rows, verify the converted data, and rehearse the application’s cutover before switching production traffic. Treat schema creation and data copying as separate jobs: your framework’s migrations can define the target schema, while a loader such as pgloader moves data into it. The main risk is assuming SQLite’s declared column types guarantee that every stored value already fits the PostgreSQL type your application expects.

What changes when you move from SQLite to PostgreSQL?

SQLite is flexibly typed: a value’s storage class belongs to the value, not necessarily to its column. As the SQLite documentation on datatypes puts it, “The datatype of a value is associated with the value itself, not with its container.” SQLite values can be NULL, INTEGER, REAL, TEXT, or BLOB; apart from an INTEGER PRIMARY KEY, a column can contain values from any storage class. SQLite STRICT tables, introduced in SQLite 3.37.0, provide stricter behavior, but an existing application should not be assumed to use them.

PostgreSQL has defined column types and constraints, so data that SQLite accepted may fail to load or may need conversion. For example, SQLite stores booleans as integers and has no dedicated date/time storage class. Date and time values may be represented as text, real Julian-day numbers, or integer Unix timestamps. Decide what those values mean to your application and map them deliberately to PostgreSQL types; the PostgreSQL 18 data type reference describes the target types.

Choose who owns the PostgreSQL schema

Pick one clear schema-creation path. For an ORM-managed application, the usual fit is to have the framework create the target schema from its version-controlled migration history, then load the existing data. Django describes migrations as “a version control system for your database schema” and applies them with its migrate command. Check the documentation for your installed framework version and use the application’s actual migration files.

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Do not casually let both the framework and loader create competing schemas. pgloader supports options including schema-only and data-only loads, giving you a way to separate those responsibilities.

Migration steps

1. Inventory the application and SQLite database

Record the application, framework, and database adapter versions, plus the current schema and migration state. Inventory tables, indexes, constraints, triggers, and views. For every type-sensitive column, inspect actual values, not only its declared type. Focus on booleans, dates and times, numeric precision, identifiers, nulls, blobs, text encoding assumptions, and values the application may have relied on SQLite to coerce.

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2. Prepare a disposable PostgreSQL target

Configure the PostgreSQL driver and connection settings in a migration or test environment, then create a target database you can discard and rebuild. If the framework owns the schema, apply its migrations there before loading data. If pgloader owns it, review its schema-discovery and creation options first.

Be especially careful with destructive loader settings. pgloader’s documented SQLite defaults include dropping matching target tables. Do not point an unreviewed command at a valuable database or a target whose contents you need to preserve.

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3. Configure and rehearse the transfer

pgloader’s tutorial gives this basic form:

pgloader <SQLite-source> pgsql:///<target>

Treat it as a starting point, not a universal production command. Credentials, networking, source consistency, schema ownership, and loader version depend on your deployment. For more control, pgloader command files can specify operations such as create tables, create indexes, and reset sequences. Its workflow also supports configurable casts and repeatable runs.

Review values that do not naturally match the application’s intended PostgreSQL type and configure casts or transformations explicitly. A loader can automate discovery and transfer; it cannot infer whether an ambiguous integer is a boolean, a timestamp, or an ordinary number based on your business rules.

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4. Investigate rejected rows and schema errors

Check the loader’s error behavior for the exact command and input. pgloader distinguishes stopping on errors from resuming while saving rejected rows; its general database migration behavior is to stop, while some file loads default to continuing. Do not count a partial load, skipped constraint, or rejected row as success. Fix the source data or mapping rule, then rerun the rehearsal and account for every error.

Legacy schema metadata can also be incompatible even when the rows look reasonable. pgloader’s tutorial demonstrates a SQLite schema with multiple primary-key definitions that PostgreSQL rejects. Review constraints and indexes as well as data types.

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5. Validate the target and exercise the application

After a load, compare source and target table counts and important aggregates. Then check the details most likely to reveal conversion problems:

  • Primary-key uniqueness and foreign-key relationships.
  • Nulls versus empty strings.
  • Date/time conversions and numeric values.
  • Representative application queries and the main read and write flows.

Run the application’s test suite against PostgreSQL. A successful loader exit alone does not establish that the target data, constraints, or application behavior are correct.

If you choose a CSV-based transfer instead of a direct migration tool, PostgreSQL’s COPY documentation covers client input and text, CSV, and binary formats. Its documented default for input conversion errors is to stop. Configure CSV null and empty-string handling intentionally so those values do not change meaning silently.

6. Rehearse cutover and keep a recovery path

Rehearse the final procedure using a recent, consistent copy of the source database. Decide how you will prevent or capture writes made after that copy, who authorizes the switch, and how the original SQLite database will be retained until PostgreSQL is verified. A write freeze, dual-write arrangement, or change-capture plan depends on the application architecture; these tools do not provide one universal live-replication plan for this migration.

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After switching, monitor application errors and database behavior, and document how to recover if the target does not behave as expected. Keep the SQLite source available until verification is complete rather than deleting it when the initial load command exits successfully.

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Common migration pitfalls

  • Trusting declared SQLite types: inspect actual stored values and decide how mixed or unexpected values should map.
  • Treating schema migration as data migration: framework migrations build schema history; they do not, by themselves, copy the existing SQLite rows.
  • Letting two tools own the schema: decide whether the framework or pgloader creates tables and indexes, then configure the other tool accordingly.
  • Ignoring partial loads: inspect rejected rows and constraints, repair the cause, and repeat the rehearsal until all data is accounted for.
  • Switching after one successful load: compare data, run application tests, and rehearse the production cutover and recovery procedure.

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