Paradox dBase Reader Guide: Importing Paradox Tables into Excel or SQL

How to Use Paradox dBase Reader to Extract Data from Paradox DatabasesParadox databases were once a popular desktop database format, commonly used in legacy business applications. Today you may encounter Paradox (.db, .dbt, .px, .mb) files when migrating systems, recovering archived data, or integrating old applications with modern tools. A Paradox dBase reader lets you open, browse, and extract table data without requiring the original application. This guide explains how Paradox files are structured, which tools to use, and step-by-step methods to extract data reliably and safely.

What is a Paradox database?

Paradox is a desktop relational database format originally developed by Borland. Typical Paradox table files include:

• .db — table structure and records (main data file)
• .px — primary index file
• .xg? / .yg? — secondary index files (various formats)
• .mb — memo file container for large text/blobs
• .dbt — legacy memo/text file (depending on version)

Paradox tables store typed columns (numeric, character, date/time, logical, etc.), indices for fast lookup, and memo fields for long text. File versions differ across Paradox releases (4.x–7.x and later), so compatibility matters when choosing a reader.

Choosing a Paradox dBase reader: options and considerations

Pick a reader based on your needs: one-off extraction, batch conversions, or integration into ETL pipelines.

Key considerations:

• Compatibility with the Paradox version you have (Paradox 4–7 and later).
• Support for memo files (.mb/.dbt) and indices (.px).
• Ability to export to CSV, Excel, SQL INSERTs, or direct database imports (SQLite, MySQL, PostgreSQL).
• Command-line support for automation vs. GUI for manual inspection.
• Data fidelity (preserve encodings, date/time formats, numeric precision).

Common tools:

• Dedicated commercial readers (often with broad version support and GUI).
• Open-source utilities (e.g., libraries or command-line tools that read Paradox).
• ODBC/JDBC drivers that expose Paradox tables as relational sources.
• Conversion services or specialized ETL tools.

Preparing to extract data

1. Gather all related files: Always collect the table’s .db and any associated .mb/.dbt, .px, and index files from the same folder. Missing memo or index files can cause data loss or incomplete reads.
2. Make backups: Work on copies of the files to avoid accidental corruption.
3. Identify encoding and locale: Older Paradox files may use DOS/ANSI encodings or locale-specific date formats. Note the likely code page (e.g., CP866, CP1251) if text looks garbled.
4. Check Paradox version if possible: File metadata or original application notes may indicate the Paradox release; if not available, you may need to try multiple readers.

Step-by-step: Extracting data with a GUI Paradox reader

This method fits users who prefer point-and-click tools.

1. Install a reputable Paradox dBase reader (commercial or open-source) that lists support for your file version.
2. Launch the application and open the folder containing your Paradox files (many readers require the folder, not the single .db file).
3. Select the table you want to inspect. The reader should display field names, types, and sample records.
4. Verify memo fields: Confirm that long text fields appear; if they’re empty or truncated, the memo file may be missing or mismatched.
5. Export the table:
   • Choose CSV or Excel for simple consumption. Use UTF-8 (or the appropriate code page) to preserve non-ASCII text.
   • For database migration, choose “Export to SQL” or “Export to SQLite/MySQL/PostgreSQL” if supported.
6. Check the exported file for correct encoding, date formats, numeric precision, and null handling. Make adjustments in export options as needed (e.g., change field delimiters, quote characters, date format).

Step-by-step: Extracting data with command-line tools or libraries

Use this for automation, batch conversions, or when integrating into scripts.

1. Install a command-line Paradox reader or library (Python, Node.js, or other). Popular approaches:
   • Python libraries that read Paradox file formats.
   • Tools that convert Paradox to CSV or SQL from the terminal.
2. Place your Paradox files in a working directory and make backups.
3. Run the conversion command. Example (pseudocode for a hypothetical tool):

   
   paradox2csv --input /path/to/table --output table.csv --encoding cp1251 

4. For libraries (e.g., Python), load the table, iterate records, and write to the target format:
   • Use appropriate decoding for text fields.
   • Handle memo fields by ensuring the memo file is accessible and matched.
   • Convert dates to ISO 8601 if target systems need it.
5. Validate results by sampling rows and checking types and values.

Importing into modern databases

If you need the Paradox table inside a relational DBMS:

1. Export to CSV or generate SQL INSERT statements with the reader or conversion tool.
2. Create a target table schema matching field names and types (map Paradox types to SQL types: character → VARCHAR, numeric → DECIMAL/DOUBLE, date → DATE/DATETIME, logical → BOOLEAN, memo → TEXT).
3. Use bulk import (LOAD DATA, COPY, or a DB client) to load CSVs. For large datasets, disable indexes before import and rebuild afterwards for speed.
4. Verify constraints, nulls, and special values. Convert date formats where necessary.

Handling common issues

• Missing memo files (.mb/.dbt): Memo fields may appear blank. Try to locate the correct memo file (same base filename) or use recovery tools that can reconstruct text from raw files.
• Encoding problems: If text appears scrambled, try different code pages (CP1252, CP866, CP1251, UTF-8). Many readers let you specify encoding on import/export.
• Corrupt or inconsistent index files (.px): Index files can be rebuilt by many readers or ignored; rebuilding may change record ordering but won’t generally alter data.
• Locked or proprietary-encrypted files: Some Paradox databases used application-specific locking or encryption. In those cases, consult the original application or a professional data recovery service.

Automation and best practices

• Script conversions for repeatability; log each run and validate row counts.
• Preserve original timestamps and filenames for audit trails.
• Keep a mapping document of Paradox field names to new schema fields and any transformations applied (encoding changes, date normalization, numeric rounding).
• For mission-critical migrations, run parallel imports and reconciliation queries to confirm parity between the source and the target.

Quick checklist before finishing a migration

• Did you back up original Paradox files?
• Did you confirm memo fields and indices are present and readable?
• Is the text encoding correct in the exported data?
• Are dates normalized to your target format?
• Did you validate row counts and sample values after import?
• Have you documented transformations and kept a copy of exported files?

Conclusion

Using a Paradox dBase reader to extract data is straightforward when you prepare carefully: gather all related files, choose a reader compatible with your Paradox version, and verify encodings and memo files. For single tables, GUI tools and exports to CSV/Excel work well. For repeated or large-scale migrations, use command-line tools and automated scripts to ensure repeatability and validation. With proper preparation and validation you can reliably recover and migrate legacy Paradox data into modern systems.