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Move an application from SQLite to PostgreSQL in two controlled stages: create the target schema using one clear owner, then transfer and validate the existing data. SQLite’s flexible typing means a successful load alone does not prove the data has the types, relationships or behavior your application expects.
Before you migrate: inventory the application and its data
Record the application version, framework and database-adapter versions, schema, indexes, constraints, triggers, views and framework migration state. Also identify how the application connects to the database and which code paths read or write important tables.
SQLite’s documentation explains that “The datatype of a value is associated with the value itself, not with its container.” A column declaration therefore does not guarantee that every stored value has the same type. SQLite values can be NULL, INTEGER, REAL, TEXT or BLOB, and columns other than an INTEGER PRIMARY KEY can hold values from any storage class. Review the [SQLite documentation on datatypes] alongside the actual values in the database.
- Booleans: SQLite has no separate Boolean storage class; Boolean values are represented as integers. Confirm what the application considers true and false before mapping them to PostgreSQL.
- Dates and times: SQLite has no dedicated date/time storage class. Values may be stored as text, real Julian-day numbers or integer Unix timestamps. Choose a PostgreSQL representation and verify conversions against real application data.
- Numbers and identifiers: Check for fractional values in integer-like columns, precision or range issues, and identifiers whose type or formatting matters to the application.
- Text, NULLs and blobs: Inspect encoding assumptions, empty strings, NULLs and binary values, including any behavior that depended on SQLite coercion.
SQLite 3.37.0 introduced STRICT tables, but do not assume an existing database uses them; check the source schema and SQLite version.
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Choose who owns the PostgreSQL schema
Keep schema creation separate from copying rows. If the application’s ORM migrations are authoritative, create the PostgreSQL database and apply the application’s version-controlled migrations first. Django describes migrations as “a version control system for your database schema” and uses the migrate command to apply them. Consult the [Django migrations documentation] and check commands against the version installed by your application.
Alternatively, a database migration tool such as pgloader can discover SQLite schema objects and create tables and indexes while transferring data. It also supports loading data into an existing schema. Choose one schema owner rather than letting the framework and loader independently create or alter competing versions of the target schema. The [pgloader SQLite reference] describes its schema and loading options.
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| Approach | Useful when | What to review |
|---|---|---|
| Apply framework migrations, then load data | The application’s ORM migration history defines the intended PostgreSQL schema. | Confirm source columns and values fit the target schema; configure casts where needed. pgloader can load into a pre-created schema. |
| Let pgloader discover the schema and transfer data | A direct database-level migration is appropriate for the application. | Review discovered types, indexes and constraints, and add mapping rules where SQLite data or schema is not portable as-is. |
Rehearse the transfer against a disposable target
Configure a migration environment to use a PostgreSQL test database and the application’s PostgreSQL driver and connection settings. Use a disposable target while learning the loader’s behavior: pgloader’s documented SQLite defaults include dropping matching target tables. Understand the command options before running against any database containing valuable data.
The pgloader tutorial shows this basic form:
pgloader <SQLite-source> pgsql:///<target>
Treat it as a starting point, not a complete production command. Credentials, network access, source consistency, schema ownership and loader version depend on the deployment. For more control, pgloader command files can specify options such as create tables, create indexes and reset sequences. Its [command reference] documents the available options.
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Review and configure casts when source values do not match the types expected by the PostgreSQL schema. pgloader supports user-defined casting rules and transformations, but it cannot infer the application’s intended meaning for ambiguous values. Use the [PostgreSQL 18 data type reference] to check target types; the current documentation URL can move as PostgreSQL releases change.
Handle load errors explicitly
Check the error policy for the specific pgloader command and input. Its general database migration behavior is to stop on error, while some file loads default to continuing; the documentation distinguishes stopping from resuming while saving rejected rows. Do not accept a load as complete if rows were rejected or constraints were skipped.
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- Inspect the reported table, row and error rather than treating a nonzero or apparently successful process exit as the whole result.
- Determine whether the problem is a source value, an incompatible schema or an incorrect cast.
- Repair the data or mapping rule, then repeat the rehearsal against a clean or deliberately reset test target.
- Confirm that the next run has no unexplained rejected rows or skipped constraints.
Automation does not guarantee schema portability: pgloader’s tutorial demonstrates an SQLite schema with multiple primary-key definitions that PostgreSQL rejects. Review the source schema and target constraints before production loading.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Validate the target database and application
After loading, compare source and target table counts and important aggregate values. Check primary-key uniqueness, foreign-key relationships, NULL and empty-string treatment, date/time conversions, numeric values and representative application queries. These checks help reveal conversion and constraint problems that a completed load command cannot rule out.
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- Run the application’s test suite against PostgreSQL.
- Exercise the main read and write flows, including cases involving dates, booleans, nullable values and relationships.
- Check that inserts and updates behave as expected, including identifier generation and sequence values where applicable.
- Investigate any mismatch before treating the target as ready.
If you use CSV as an intermediate transfer instead of a direct migration tool, PostgreSQL’s COPY supports client input and text, CSV or binary formats. Its documented default is to stop on input conversion errors; configure CSV NULL and empty-string handling deliberately. See the [PostgreSQL COPY documentation].
Plan cutover and recovery
Rehearse the final procedure using a recent, consistent copy of the SQLite database. A rehearsal does not account for writes made afterward, so the final plan must address how those writes are prevented or captured before switching the application to PostgreSQL.
- Choose and document the final source snapshot or write-freeze procedure, including who authorizes the switch.
- Run the rehearsed schema and data steps, then repeat the key validation checks on the final target.
- Point the application at PostgreSQL and monitor application errors and database behavior.
- Keep the SQLite source and a documented recovery path until the target is verified.
There is no universal live-replication or change-capture procedure for this move: downtime, write-freeze, dual-write or capture plans depend on the application architecture. Do not delete the SQLite source merely because the initial load command exited successfully.
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