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Get the Report →Load Odoo Data to a Database Using Embulk
Use CData JDBC drivers with the open source ETL/ELT tool Embulk to load Odoo data to a database.
Embulk is an open source bulk data loader. When paired with the CData JDBC Driver for Odoo, Embulk easily loads data from Odoo to any supported destination. In this article, we explain how to use the CData JDBC Driver for Odoo in Embulk to load Odoo data to a MySQL dtabase.
With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Odoo data. When you issue complex SQL queries to Odoo, the driver pushes supported SQL operations, like filters and aggregations, directly to Odoo and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
About Odoo Data Integration
Accessing and integrating live data from Odoo has never been easier with CData. Customers rely on CData connectivity to:
- Access live data from both Odoo API 8.0+ and Odoo.sh Cloud ERP.
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Extend the native Odoo features with intelligent handling of many-to-one, one-to-many, and many-to-many data properties. CData's connectivity solutions also intelligently handle complex data properties within Odoo. In addition to columns with simple values like text and dates, there are also columns that contain multiple values on each row. The driver decodes these kinds of values differently, depending upon the type of column the value comes from:
- Many-to-one columns are references to a single row within another model. Within CData solutions, many-to-one columns are represented as integers, whose value is the ID to which they refer in the other model.
- Many-to-many columns are references to many rows within another model. Within CData solutions, many-to-many columns are represented as text containing a comma-separated list of integers. Each value in that list is the ID of a row that is being referenced.
- One-to-many columns are references to many rows within another model - they are similar to many-to-many columns (comma-separated lists of integers), except that each row in the referenced model must belong to only one in the main model.
- Use SQL stored procedures to call server-side RFCs within Odoo.
Users frequently integrate Odoo with analytics tools such as Power BI and Qlik Sense, and leverage our tools to replicate Odoo data to databases or data warehouses.
Getting Started
Configure a JDBC Connection to Odoo Data
Before creating a bulk load job in Embulk, note the installation location for the JAR file for the JDBC Driver (typically C:\Program Files\CData\CData JDBC Driver for Odoo\lib).
Embulk supports JDBC connectivity, so you can easily connect to Odoo and execute SQL queries. Before creating a bulk load job, create a JDBC URL for authenticating with Odoo.
To connect, set the Url to a valid Odoo site, User and Password to the connection details of the user you are connecting with, and Database to the Odoo database.
Built-in Connection String Designer
For assistance in constructing the JDBC URL, use the connection string designer built into the Odoo JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.odoo.jar
Fill in the connection properties and copy the connection string to the clipboard.

Below is a typical JDBC connection string for Odoo:
jdbc:odoo:User=MyUser;Password=MyPassword;URL=http://MyOdooSite/;Database=MyDatabase;
Load Odoo Data in Embulk
After installing the CData JDBC Driver and creating a JDBC connection string, install the required Embulk plugins.
Install Embulk Input & Output Plugins
- Install the JDBC Input Plugin in Embulk.
https://github.com/embulk/embulk-input-jdbc/tree/master/embulk-input-jdbc - In this article, we use MySQL as the destination database. You can also choose SQL Server, PostgreSQL, or Google BigQuery as the destination using the output Plugins.
https://github.com/embulk/embulk-output-jdbc/tree/master/embulk-output-mysqlembulk gem install embulk-output-mysql
embulk gem install embulk-input-jdbc
With the input and output plugins installed, we are ready to load Odoo data into MySQL using Embulk.
Create a Job to Load Odoo Data
Start by creating a config file in Embulk, using a name like odoo-mysql.yml.
- For the input plugin options, use the CData JDBC Driver for Odoo, including the path to the driver JAR file, the driver class (e.g. cdata.jdbc.odoo.OdooDriver), and the JDBC URL from above
- For the output plugin options, use the values and credentials for the MySQL database
Sample Config File (odoo-mysql.yml)
in:
type: jdbc
driver_path: C:\Program Files\CData[product_name] 20xx\lib\cdata.jdbc.odoo.jar
driver_class: cdata.jdbc.odoo.OdooDriver
url: jdbc:odoo:User=MyUser;Password=MyPassword;URL=http://MyOdooSite/;Database=MyDatabase;
table: "res_users"
out:
type: mysql
host: localhost
database: DatabaseName
user: UserId
password: UserPassword
table: "res_users"
mode: insert
After creating the file, run the Embulk job.
embulk run odoo-mysql.yml
After running the the Embulk job, find the Salesforce data in the MySQL table.
Load Filtered Odoo Data
In addition to loading data directly from a table, you can use a custom SQL query to have more granular control of the data loaded. You can also perform increment loads by setting a last updated column in a SQL WHERE clause in the query field.
in:
type: jdbc
driver_path: C:\Program Files\CData[product_name] 20xx\lib\cdata.jdbc.odoo.jar
driver_class: cdata.jdbc.odoo.OdooDriver
url: jdbc:odoo:User=MyUser;Password=MyPassword;URL=http://MyOdooSite/;Database=MyDatabase;
query: "SELECT name, email FROM res_users WHERE [RecordId] = 1"
out:
type: mysql
host: localhost
database: DatabaseName
user: UserId
password: UserPassword
table: "res_users"
mode: insert
More Information & Free Trial
By using CData JDBC Driver for Odoo as a connector, Embulk can integrate Odoo data into your data load jobs. And with drivers for more than 200+ other enterprise sources, you can integrate any enterprise SaaS, big data, or NoSQL source as well. Download a 30-day free trial and get started today.