GizmoSQL

iOS Universel / developpeurs

The GizmoSQL app turns your iPhone or iPad into a high-performance SQL database server using the Arrow Flight SQL protocol — the same columnar data transfer standard used in enterprise analytics.

START A SERVER IN SECONDS
Choose DuckDB or SQLite as your backend, tap Start, and you have a fully functional database server running on your device. Connect from laptops, desktops, or other devices on your network using any Arrow Flight SQL client — including JDBC, ADBC (Go, Python, C++), ODBC, and Node.js drivers.

DUCKLAKE COMPATIBLE
Access your DuckLake using your GizmoSQL mobile server. The PostgreSQL and httpfs extensions are pre-loaded so you can connect to and query your data lake seamlessly.

BUILT-IN SQL CLIENT
Write and execute SQL queries directly on your device with a terminal-style interface. Features include syntax highlighting, box-drawing table output, query timing, and automatic result pagination for large datasets.

DATA BROWSER
Explore your database visually. Navigate catalogs, schemas, and tables. View column names, types, and constraints. Preview data and manage tables — all without writing a query.

KEY FEATURES
- DuckDB and SQLite database backends
- Arrow Flight SQL protocol for high-performance columnar data transfer
- Automatic TLS encryption with self-signed certificates
- Username/password authentication with JWT session tokens
- Configurable query timeout, logging, and init SQL commands
- Export database files via the Files app — copy to iCloud Drive, AirDrop, or any sharing method
- Real-time server logs with color-coded severity levels
- Active session monitoring

BUILT FOR ANALYTICS
DuckDB is an analytical database engine optimized for complex queries over large datasets. Combined with Arrow Flight SQL's columnar transport, GizmoSQL delivers fast query results whether you're running TPC-H benchmarks or exploring real-world data on the go.

CONNECT FROM ANYWHERE ON YOUR NETWORK
Once the server is running, any device on the same Wi-Fi network can connect using the displayed connection string. GizmoSQL supports the full Arrow Flight SQL protocol including prepared statements, transactions, catalog metadata, and bulk data ingest.

See: https://gizmodata.com/gizmosql for more details.
View the source code at: https://github.com/gizmodata/gizmosql

Quoi de neuf dans la dernière version ?

GetTables schema now carries real per-column metadata. The Arrow schema returned via Flight SQL GetTables with include_schema=true previously came straight from SELECT * FROM t LIMIT 0, which marks every field nullable and carries no DDL metadata. DuckDBTablesWithSchemaBatchReader now also queries duckdb_columns() per table (with proper ? parameter binding) and applies:
Field.nullable ← real NOT NULL constraint (fixes DBeaver's column-browser Nullable checkbox).
Metadata ARROW:FLIGHT:SQL:REMARKS ← column comment (populates JDBC REMARKS).
Metadata ARROW:FLIGHT:SQL:IS_AUTO_INCREMENT ← "1" when the default starts with nextval(, else "0" (populates JDBC IS_AUTOINCREMENT).
Metadata GIZMOSQL:COLUMN_DEFAULT ← the column's default expression, exposed through the GizmoSQL JDBC driver v1.6.1+ as JDBC COLUMN_DEF. Fully backward-compatible: all three metadata keys are ignored by old clients; the standard Flight SQL JDBC driver picks up REMARKS + IS_AUTO_INCREMENT for free (they are upstream Apache Arrow Flight SQL spec keys).

_gizmosql_system system catalog (DuckDB backend). Server init SQL now ATTACH ':memory:' AS _gizmosql_system and creates two JDBC-shaped metadata helper views inside it, so Flight SQL clients can recover metadata that the Flight SQL protocol itself does not expose:

Fixed

DECIMAL prepared-statement parameter binding aborts the server process. Prior to v1.22.0, executing a prepared INSERT / UPDATE bound to a DuckDB DECIMAL column could trigger Arrow's ValidateDecimalPrecision check and SIGABRT the gizmosql_server process (exit 134). Surface symptom on the client was a raw UNAVAILABLE: Network closed for unknown reason / gRPC channel termination — the server process just disappeared mid-query. Three distinct bugs in duckdb_statement.cpp::GetDataTypeFromDuckDbType were fixed together: the DECIMAL arm never populated width/scale from the DuckDB type (hardcoded 0), the arrow::smallest_decimal(...) call had its arguments flipped ((scale, width) instead of (width, scale)), and returning a Decimal32/Decimal64 type is not accepted by the Arrow Java JDBC client (which only supports Decimal128 / Decimal256). The server now emits Decimal128(width, scale) for precisions 1–38, Decimal256(width, scale) for precision > 38, and falls back to Decimal256(38, scale) when DuckDB reports width == 0 (unresolved parameter placeholders in statements like INSERT INTO t(decimal_col) VALUES (?)). Regression coverage lives in the GizmoSQL JDBC driver repo's GizmoSqlIntegrationIT.testDecimalParameterRoundTrip, exercised against gizmodata/gizmosql:latest on every JDBC CI run.

Bulk ingest with temporary=True (issue #158): Repeated adbc_ingest(..., temporary=True) calls (or any Flight SQL CommandStatementIngest with temporary=true) no longer fail with Catalog Error: Table with name "..." already exists! (for create_append/replace) or Table: "..." does not exist (for create then append). The server's table-existence check previously only consulted the current database catalog, so temporary tables — which DuckDB stores in the implicit temp.main catalog — were invisible to the lookup. TableExists() now scopes to temp.main when the ingest is temporary. Thanks again to @fromm1990 for the report and reproducer.