Troubleshooting Common PostgresToSqlite Migration Issues

Migrating Data with PostgresToSqlite: A Step-by-Step GuideMigrating data from PostgreSQL to SQLite can be useful for creating lightweight local copies for development, testing, offline apps, or distribution with an application. PostgresToSqlite is a tool designed to simplify this process by handling schema conversion, data extraction, and type mapping between PostgreSQL and SQLite. This guide walks through planning, preparing, executing, and validating a migration using PostgresToSqlite, with tips for common pitfalls and performance considerations.

Why migrate from PostgreSQL to SQLite?

Portability: SQLite stores the entire database in a single file, making distribution and backups simple.
Simplicity: No server process required for local apps or desktop tools.
Testing and CI: Lightweight databases speed up unit tests and continuous integration.
Offline access: Mobile and client-side applications often prefer SQLite for local storage.

Before you start: planning and limitations

Data model compatibility: PostgreSQL supports advanced types (arrays, JSONB, enums, custom types, full-text search, materialized views, stored procedures) that SQLite either lacks or implements differently. Decide how to map or flatten these features.
Size and performance: SQLite works best for moderate data sizes and lower-concurrency workloads. Large datasets may produce a very large file and slower queries.
Constraints and indexes: SQLite supports primary keys, unique constraints, and basic indexes, but lacks some constraint and index features present in PostgreSQL (partial indexes, expression indexes that use complex functions).
Transactions and concurrency: SQLite uses database-level locking for writes; plan for this if multiple writers are expected.
Encoding and collations: Ensure text encodings and collations are compatible.

Tip: Start by migrating a representative subset of the database to validate schema mappings and performance before attempting a full migration.

Prerequisites

Access to the PostgreSQL server and credentials with sufficient privileges to read schema and data.
PostgresToSqlite installed (either via pip, a binary, or included in your project). Example: pip install postgres-to-sqlite (adjust to actual package name/version).
Python and SQLite3 client tools available if you need to inspect the output file.
Sufficient disk space for the resulting SQLite file plus temporary exports.

Step 1 — Inspect the PostgreSQL schema and data

List tables and sizes to identify large tables and special types:
- Use pg_catalog and information_schema queries, or tools like pgcli/psql.
Look for columns using:
- Arrays, JSONB/JSON, UUID, bytea (binary), enums, ranges, geometric types, and user-defined types.
Identify triggers, stored procedures, and views that may need reimplementation or removal.

Example queries:

Table sizes:


SELECT relname AS table, pg_total_relation_size(relid) AS size FROM pg_catalog.pg_statio_user_tables ORDER BY size DESC;

Columns with special types:


SELECT table_schema, table_name, column_name, data_type FROM information_schema.columns WHERE data_type IN ('ARRAY','json','jsonb','uuid','bytea','USER-DEFINED');

Step 2 — Decide on type and schema mapping

Common mappings:

integer, bigint → INTEGER
numeric, decimal → REAL or TEXT (choose TEXT for exact precision; use numeric strings)
text, varchar → TEXT
boolean → INTEGER (0/1) or TEXT (’t’/‘f’) — SQLite has BOOLEAN affinity but no strict type
json/jsonb → TEXT (store JSON as text) or use a JSON1 extension if querying JSON
uuid → TEXT
bytea → BLOB
arrays → TEXT (serialized) or a separate child table to normalize arrays
enums → TEXT or create check constraints to emulate enums

Decide how to handle:

Auto-increment: PostgreSQL sequences → SQLite INTEGER PRIMARY KEY AUTOINCREMENT (if needed)
Foreign keys: SQLite supports foreign key constraints but they are disabled by default; enable with PRAGMA foreign_keys = ON;
Indexes: Recreate simple indexes; complex or partial indexes may need alternative approaches.

Step 3 — Configure PostgresToSqlite

Typical options to set:

Source connection string (Postgres): postgres://user:pass@host:port/dbname
Destination file path for SQLite database
Table filters: include/exclude tables or schemas
Type mapping rules and custom transformations (e.g., serialize JSONB, convert UUID)
Batch size for inserts and transaction settings to balance speed and memory
Whether to copy indexes, constraints, and foreign keys

Example CLI usage (illustrative — check your PostgresToSqlite docs for exact flags):

postgrestosqlite --source "postgres://user:pass@host:5432/db" --dest ./data.db    --include-schemas public --exclude-tables audit_logs    --map-json-to text --batch-size 5000 --threads 4

Step 4 — Run a dry run on a subset

Export a few critical tables or a limited number of rows to validate schema mappings and application compatibility.
Inspect the generated SQLite schema and test common queries from your application.
Check for data truncation, encoding issues, and failed type conversions.

Commands:

Use –limit or –tables flags to target a subset.
Open the resulting SQLite with sqlite3 or a GUI (DB Browser for SQLite) to inspect tables, indexes, and sample rows.

Step 5 — Perform the full migration

Ensure you have a backup of the PostgreSQL database before running a full export.
Run PostgresToSqlite with your configured options. For large datasets:
- Use batching and transactions to prevent memory spikes.
- Consider exporting large tables separately and importing them with optimized PRAGMA settings in SQLite (see performance tips).
Monitor logs for warnings about skipped objects or failed conversions.

Performance tuning and SQLite PRAGMAs

To speed up large imports, wrap writes with recommended pragmas:

PRAGMA synchronous = OFF; PRAGMA journal_mode = WAL; PRAGMA cache_size = -200000; -- use larger cache PRAGMA temp_store = MEMORY;

Disable foreign keys during import if many inserts will be performed, then re-enable and validate after:
```
PRAGMA foreign_keys = OFF; -- import... PRAGMA foreign_keys = ON; 
```

Step 6 — Recreate indexes and constraints

Some tools drop indexes during bulk import to speed up writes; recreate them afterward.
Verify primary keys and unique constraints are preserved or redefined.
For foreign keys, ensure they are present if your app depends on them, and validate referential integrity.

Step 7 — Validate the migrated data

Row counts: Compare table row counts between Postgres and SQLite.
Checksums: Compute checksums (e.g., MD5 of ordered concatenation of rows) for critical tables.
Spot checks: Query sample records and edge cases (NULLs, max lengths, special characters).
Application tests: Run application or unit tests against the SQLite database to surface query compatibility issues.

Example row count check:

-- PostgreSQL SELECT count(*) FROM public.users; -- SQLite SELECT count(*) FROM users;

Handling special cases

JSONB: Store as TEXT, and if you need JSON queries, enable SQLite JSON1 extension and adapt queries.
Arrays: Prefer normalizing into child tables or store as delimited TEXT, document the format.
Large objects (bytea): Export as BLOBs and ensure clients can read them.
Sequences: If application relies on specific sequence values, migrate sequence states to appropriate AUTOINCREMENT settings.

Troubleshooting common issues

Encoding errors: Ensure client encoding is UTF-8 during export/import.
Out-of-range numeric values: Store as TEXT if precision matters.
Missing indexes causing slow queries: Recreate critical indexes; analyze slow queries and add indexes accordingly.
Constraints not enforced: Ensure PRAGMA foreign_keys = ON and recreate any needed triggers or checks.

After migration: maintenance and distribution

Compact the database: VACUUM to reclaim space and optimize file size.
Test app performance and optimize indexes or queries for SQLite.
If distributing the DB, consider encrypting the file or shipping read-only copies.
Document any schema differences and migration caveats for future maintenance.

Example workflow (summary)

Audit PostgreSQL schema and data types.
Define mapping rules and prepare transformations.
Run PostgresToSqlite on a subset for testing.
Tune mapping, PRAGMAs, and performance settings.
Execute full migration and recreate indexes.
Validate data and run application tests.
VACUUM and distribute.

Final notes

Migrating from PostgreSQL to SQLite is straightforward for many schemas, but requires attention for advanced Postgres features and large datasets. PostgresToSqlite automates much of the work, but planning, testing, and validation are essential to ensure a reliable result.