Free online YAML to MDB converter

A legacy Microsoft Access application may require an .mdb database, while configuration exports and structured records often arrive as .yaml. Conversion is therefore a data-model migration: YAML values must be assigned to Access tables, columns, and relationships rather than simply renamed.

What the YAML format is

YAML is a human-readable serialization format used for configuration files, deployment manifests, application data, and structured exports. Common producers include Kubernetes, Docker Compose, Ansible, GitHub Actions, and custom Python, Ruby, or JavaScript programs.

A YAML document can contain mappings, sequences, nested objects, numbers, Boolean values, nulls, and multiline strings. It has no fixed database schema, primary-key system, or standard mapping to relational tables. A file such as users.yaml may represent one object, a list of objects, or several unrelated sections.

What the MDB format is

MDB is the Microsoft Access database format used primarily by Access 2000–2003 and older applications. It stores tables, indexes, relationships, queries, forms, reports, and database metadata in one file.

MDB is useful when a legacy program, Access installation, reporting workflow, or ODBC connection specifically requires an Access database. Its relational tables and typed columns are better suited than YAML for filtering, joins, indexed lookups, and multi-record editing, but the format has compatibility limits and is generally replaced by .accdb in newer Access versions.

How to actually convert YAML to MDB

Use the built-in online converter

You can convert the file on 101convert.com for free without installing software. Choose YAML as the source format and MDB as the target, upload the .yaml or .yml file, start the conversion, and download the resulting .mdb file when processing finishes. Inspect the generated tables and column types in Microsoft Access before using the database in production.

Convert locally with Microsoft Access

1. Open the YAML file in a YAML-aware editor and identify its top-level records. A sequence of similarly shaped mappings is the easiest structure to import.
2. Flatten or normalize nested data. For example, store each user in a Users table and each user's repeated address or order items in a related table with a foreign key.
3. Export each flat collection as CSV, using UTF-8 encoding and a consistent delimiter. Do not use commas inside unquoted values.
4. Create a blank database in Microsoft Access and select External Data → New Data Source → From File → Text File.
5. Import each CSV as a new table, choose the delimiter and text qualifier, select field types, and define a primary key where appropriate.
6. Create relationships through Database Tools → Relationships, then save the database in the MDB format. In newer Access versions, use File → Save As → Access 2000–2003 Database (*.mdb) or the equivalent legacy database option.

Automate the migration with Python

For repeatable conversions, parse YAML with PyYAML and write records through the Microsoft Access ODBC driver. Install the parser with python -m pip install pyyaml, then use a script that creates tables before inserting rows:

import yaml
import pyodbc

with open("users.yaml", encoding="utf-8") as stream:
    records = yaml.safe_load(stream)

connection = pyodbc.connect(
    r"DRIVER={Microsoft Access Driver (*.mdb, *.accdb)};DBQ=C:\\data\\output.mdb;"
)
cursor = connection.cursor()
cursor.execute("CREATE TABLE Users (id INTEGER, name TEXT(255), email TEXT(255))")
for record in records:
    cursor.execute(
        "INSERT INTO Users (id, name, email) VALUES (?, ?, ?)",
        record.get("id"), record.get("name"), record.get("email")
    )
connection.commit()
connection.close()

This method requires a writable Access ODBC driver and is most practical on Windows with Microsoft Access Database Engine installed. Replace the table definition and field mapping with the actual YAML schema; nested mappings and lists require separate tables rather than direct insertion into a single text column.

Quality, compatibility, and limitations

• YAML dates, timestamps, nulls, and numeric-looking strings can be interpreted differently by parsers. Validate the parsed Python types before assigning Access column types such as DATETIME, INTEGER, DOUBLE, or TEXT.
• MDB text fields have length limits: use TEXT(n) for ordinary values and LONGTEXT for large content where supported. Check Unicode behavior when the target application uses an older Access driver.
• YAML comments, anchors, aliases, key order, and formatting are not preserved in a relational database. Preserve the original YAML separately if those details matter.
• Do not force arrays or nested objects into string columns unless the receiving application expects serialized data. Relational child tables retain searchable values and relationships.
• MDB has a 2 GB file-size limit and older Access engines may impose additional field, table, or index restrictions. Linux tools such as MDBTools are mainly intended for reading MDB files; reliable creation is usually easier through Access or the Windows ODBC driver.