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ETL Validator provides data movement and transformation capabilities for integrating data platforms across your organization. CData's JDBC driver seamlessly integrates with ETL Validator and extends its native connectivity to include MongoDB data.
This tutorial explains how to build a simple ETL validator data flow to extract data from MongoDB data and load it into an example data storage solution: SQL Server.
Accessing and integrating live data from MongoDB has never been easier with CData. Customers rely on CData connectivity to:
MongoDB's flexibility means that it can be used as a transactional, operational, or analytical database. That means CData customers use our solutions to integrate their business data with MongoDB or integrate their MongoDB data with their data warehouse (or both). Customers also leverage our live connectivity options to analyze and report on MongoDB directly from their preferred tools, like Power BI and Tableau.
For more details on MongoDB use case and how CData enhances your MongoDB experience, check out our blog post: The Top 10 Real-World MongoDB Use Cases You Should Know in 2024.
CData extends ETL Validator's data connectivity capabilities by providing the ability to add data sources that connect via CData's JDBC drivers. Connecting to MongoDB data simply requires creating a new data source in ETL Validator through CData's connectiviy suite as described below.
Begin by logging into ETL Validator to view the application dashboard.
π Access the ETL Validator dashboardCData extends the data source options within ETL Validator.
π Create a new DataSourceCData's connectivity is embedded within ETL Validator's data source options.
π CData data sourceYou will need a JDBC connection string to establish a connection to MongoDB in ETL Validator.
π CData data sourceSet the Server, Database, User, and Password connection properties to connect to MongoDB. To access MongoDB collections as tables you can use automatic schema discovery or write your own schema definitions. Schemas are defined in .rsd files, which have a simple format. You can also execute free-form queries that are not tied to the schema.
For assistance in constructing the JDBC URL, use the connection string designer built into the MongoDB JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.mongodb.jar
π Using the built-in connection string designer to generate a JDBC URL (mongodb is shown.)
A typical connection string looks like this:
jdbc:mongodb:Server=MyServer;Port=27017;Database=test;User=test;Password=Password;
To ensure the JDBC driver is licensed appropriately, copy the license file to the appropriate location:
Copy the JDBC Driver for MongoDB and lic file from "C:\Program Files\CData[product_name]\lib" to "C:\Datagaps\ETLValidator\Server\apache-tomcat\bin".
cdata.jdbc.mongodb.jar cdata.jdbc.mongodb.lic
Note: If you do not copy the .lic file with the jar, you will see a licensing error that indicates you do not have a valid license installed. This is true for both the trial and full versions.
Should you encounter any difficulties loading the CData JDBC driver class, please contact DataGap's team, and they will provide you instructions on how to load the jar file for the relevant driver.
This example will use SQL Server as a destination for MongoDB data data, but any preferred destination can be used instead.
This option is the default.
π Add SQL ServerThe details will depend on the specific target, but these details may include a URL, authentiation credentials, etc.
π Add SQL ServerConfigured data flows will appear in this window.
π Dataflows tabName your new dataflow and save it.
The details of the data movement will be configured in this panel.
π Dataflow diagramGive the new source an appropriate name and save it.
π Jira example sourceSelect the Table from the Schema option that reflects which data should be pulled from MongoDB data.
The anticipated outcome of the configured query is displayed in the Result tab.
π Query resultsSelect Switch to Diagram, then drag & drop the DB Sink as a target from the right side (under Sink options). Give the sink an appropriate name and save it.
π Data sinkChoose the Schema and table that matches the structure of the source table. For this example, the table on the target side was created to match the Source so that data flow seamlessly. More advanced schema transformation operations are beyond the scope of this article.
π Destination schemaRunning the job will take some time.
π Destination schemaReturn to the diagram to see the finished data replication job from MongoDB data to SQL Server.
π Full dataflowDownload a free, 30-day trial of the CData JDBC Driver for MongoDB and start building MongoDB-connected applications with ETL Validator. Reach out to our Support Team if you have any questions.
Download a free trial of the MongoDB Driver to get started:
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π MongoDB IconRapidly create and deploy powerful Java applications that integrate with MongoDB document databases.