dbt with Teradata

Teradata Developer Guides

ft:locale: en-US
ft:lastEdition: 2026-08-18

Teradata Developer Guides
Additional Resources
Teradata Engine Architecture and Concepts
Overview
Teradata Engine Architecture Components
Parsing Engines (PEs)
BYNET
Parallel Database Extensions (PDE)
Access Module Processors (AMPs)
Virtual Disks (Vdisks)
Node
Teradata Architecture Concepts
Linear Growth and Expandability
Teradata Parallelism
Teradata Retrieval Architecture
Teradata Data Distribution
Conclusion
Further Reading
Get Access to Teradata
Run Teradata on Your Local Machine
Run Vantage Express on VMware
Overview
Prerequisites
Installation
Download required software
Run installers
Run Vantage Express
Summary
Next steps
Further reading
Run Teradata on Your Cloud Infrastructure
Run Vantage Express on AWS
Overview
Prerequisites
Installation
Run sample queries
Optional setup
Cleanup
Next steps
Further reading
Teradata Trial
Getting started with Teradata Trial
Overview
Create a Teradata Trial account
Create an Environment
Access demos
Summary
Further reading
Connect to Teradata
Use Teradata Studio/Express on Apple Mac M1/M2/M3
Overview
Steps to follow
Summary
Configure a Teradata connection in DBeaver
Overview
Prerequisites
Add a Teradata connection to DBeaver
Optional: Logon Mechanisms
Optional: SSH tunneling
Summary
Connect to Teradata Cloud Using DBeaver and SSO (Browser Logon)
Overview
Prerequisites
Create a Teradata Connection with SSO
Running Teradata Queries in Dbeaver
Recommended DBeaver Settings for Teradata Users
Disable "Blank line is statement delimiter"
Disable Removal of Trailing Query Delimiters
Enable Line Numbers
Disable Insert Table Aliases
Use Column Names Instead of Labels
How-to
Display the Sum, Min, Max, etc. of a Column
Change Shortcut Keys
FAQ
Summary
Configure ODBC
Use Teradata with ODBC on Ubuntu
Overview
Prerequisites
Installation
Option 1: Launch an Ubuntu instance on AWS EC2
Install dependencies
Install Teradata ODBC driver
Configure ODBC
Use ODBC
Summary
Further reading
Manage Data
Query data stored in object storage
Overview
Prerequisites
Explore data with NOS
Query data with NOS
Load data from NOS into Teradata
Access private buckets
Export data from Teradata to object storage
Summary
Further reading
Select the right data ingestion solution for Teradata
Overview
High-volume ingestion, including streaming
Ingest data from object storage
Ingest data from local files
Ingest data from SaaS applications
Use data stored in other databases for unified query processing
Summary
Further Reading
Use Apache Airflow with Teradata Database
Overview
Prerequisites
Install Apache Airflow
Start Airflow Standalone
Define a Teradata connection using the Airflow CLI
Define a Teradata connection in Environment Variable
JSON format example
URI format example
Define a DAG in Airflow
Load DAG
Run DAG
Summary
Further reading
Execute dbt teradata transformation jobs in Apache Airflow using Astronomer Cosmos library
Overview
Prerequisites
Install Apache Airflow and Astronomer Cosmos
Install dbt
Setup dbt project
Configure Apache Airflow
Start Apache Airflow web server
Define Apache Airflow connection to Teradata
Define DAG in Apache Airflow
Load DAG
Run DAG
Summary
Further reading
Data Transfer from Azure Blob to Teradata Using Apache Airflow
Overview
Prerequisites
Install Apache Airflow
Configure Apache Airflow
Start Apache Airflow
Define the Apache Airflow connection to Teradata
Define a DAG in Apache Airflow
Load the DAG
Run the DAG
Transfer data from a private Azure Blob Storage container to Teradata
Summary
Further reading
Use Fivetran to load data from external sources to Teradata
Overview
Load data from Google Sheets to Teradata
Before You Begin
Prerequisites
Setup Google Sheets
Fivetran Setup: Sync from Google Sheets to Teradata
Configure Teradata as Destination
Setup Connection with Source as Google Sheets
Verify Data in Teradata
Load data from PostgreSQL to Teradata
Prerequisites
Setup PostgreSQL
Fivetran Setup: Sync from Postgres to Teradata
Configure Teradata as Destination
Setup Connection with Source as Postgres
Verify Data in Teradata
Load data from Amazon S3 to Teradata
Prerequisites
Setup Amazon S3
Fivetran Setup: Sync from Amazon S3 to Teradata
Configure Teradata as Destination
Setup Connection with Source as Amazon S3
Verify Data in Teradata
Try More Use Cases
Summary
Further reading
dbt Cloud with Teradata
Prerequisites
About the Jaffle Shop warehouse
Creating a project in dbt Cloud and connect to a Teradata environment
dbt Project setup
Import a sample dbt project to dbt Cloud
Create an environment for managing staging and production workflows for the project
Create and run a job
Summary
Further reading
dbt with Teradata
Overview
Prerequisites
Install dbt
Configure dbt
About the Jaffle Shop warehouse
Run dbt
Create raw data tables
Create the dimensional model
Test the data
Generate documentation
Summary
Further reading
dagster-teradata with Teradata
Dagster
Prerequisites
Setting Up the Project with uv
Initialize a Dagster Project
Create a New Dagster Project
Configure the pyproject.toml with Required Packages
Create Sample Data
Create a Database for the Pipeline
Define Assets for the ETL Pipeline
Register Assets in defs/__init__.py
Set Up Environment Variables
Running the Pipeline
TeradataResource Operations
1. Execute a Query (execute_query)
2. Execute Multiple Queries (execute_queries)
3. Drop a Database (drop_database)
4. Drop a Table (drop_table)
Summary
Further reading
Data Transfer from AWS S3 to Teradata Using dagster-teradata
Overview
Prerequisites
Setting Up the Project with uv
Initialize a Dagster Project
Create a New Dagster Project
Update pyproject.toml with Additional Dependencies
Step 1: Open definitions.py in src/dagster_teradata_s3/ Directory
Step 2: Implement AWS S3 to Teradata Transfer in Dagster
Explanation of the Code
Preparing Your Data
Create an S3 Bucket
Upload Sample Data
Set Environment Variables
Prepare Teradata
Running the Pipeline
Public vs Private S3 Buckets
Configure a Private S3 Bucket
Creating a Teradata AUTHORIZATION Object for Private Buckets
Step 1: Gather AWS Credentials
Step 2: Create AUTHORIZATION Object
Step 3: Reference AUTHORIZATION in Dagster Code
Important Security Notes:
Arguments Supported by s3_blob_to_teradata
Summary
Further reading
Data Transfer from Azure Blob to Teradata Using dagster-teradata
Overview
Prerequisites
Set Up the Project with uv
Initialize a Dagster Project
Create a New Dagster Project
Add the Required Dependencies
Configure the Dagster Project
Understand the Code
Resource Configuration
Operations
Job Execution
Use the Public Azure Blob Storage Dataset
Set Environment Variables
Prepare Teradata
Run the Pipeline
Start the Dagster Development Server
Access the Dagster UI
Launch the Job
Verify the Data Transfer
Transfer data from a private Blob Storage container to Teradata
Summary
Further reading
Advanced dbt use cases with Teradata
Overview
Prerequisites
Demo project setup
Data setup
Configure dbt
About the Teddy Retailers warehouse
The data models
The sources
The dbt models
Staging area
Core area
Incremental materializations
Macro assisted assertions
Teradata modifiers
Running transformations
Create dimensional model with baseline data
Test the data
Running sample queries
Mocking the ELT process
Summary
Automate Data Movement and Transformation with Airflow, Airbyte, and dbt in Teradata
Overview
Prerequisites
Demo project setup
Airbyte setup
Airflow setup
Orchestrating with Airflow
Conclusion
Use Airbyte to load data from external sources to Teradata
Overview
Prerequisites
Airbyte Cloud
Airbyte Open Source
Airbyte Configuration
Set up the Source Connection
Set up the Destination Connection
Select sync mode and schema
Configure connection
Data Sync Validation in Airbyte
Validate the data in Teradata Trial
Optional: Close and delete the connection
Summary
Further reading
Manage ELT pipelines as code with Terraform and Airbyte on Teradata
Overview
Introduction
Prerequisites
Install Terraform
Environment Preparation
Define a Data Pipeline
Configuring the variables.tf File
Sample Terraform .tfvars File
Understanding Terraform State
Execution Commands
Additional Resources
Run large bulkloads efficiently with Teradata Parallel Transporter (TPT)
Overview
Prerequisites
Install TTU
Get Sample data
Create a database
Run TPT
TPT vs. NOS
Summary
Further reading
Create Parquet files in object storage
Overview
Prerequisites
Create a Parquet file with WRITE_NOS function
Summary
Further reading
Stream Events from Redis to Teradata
Architecture
Prerequisites
Step 1: Create the event data table in Teradata
Step 2: Start Redis locally
Step 3: Set up Python environment with uv
Create pyproject.toml
Sync dependencies
Step 4: Create the event producer script
Step 5: Create the event consumer script
Step 6: Set up environment variables
Step 7: Run the streaming pipeline
Step 8: Verify the data in Teradata
Step 9: Clean up
Extending the guide
Run the producer in a loop
Add multiple consumers
Filter events by type
Monitor Redis stream
Troubleshooting
Summary
Query Azure Blob Storage from Teradata
Overview
About Teradata NOS
Prerequisites
Location String Format
Step 1: Configure Access
Public containers
Private containers
Step 2: Explore the Schema
Step 3: Query Data with READ_NOS
Step 4: Create a Foreign Table (Optional)
Step 5: Load Data into Teradata (Optional)
About Azure Open Datasets
Configure a Teradata connection in DataHub
Overview
Prerequisites
Setup DataHub
Add a Teradata connection to DataHub
Summary
Further reading
Ingest and Catalog Data from Teradata to Amazon S3 with AWS Glue Scripts
Overview
Prerequisites
Loading of test data
Amazon AWS setup
Create an Amazon S3 Bucket to Ingest Data
Create an AWS Glue Catalog Database for Storing Metadata
Store Teradata credentials in AWS Secrets Manager
Create an AWS Glue Service Role to Assign to ETL Jobs
Create a connection to a Teradata Instance in AWS Glue
Create an AWS Glue Job
Draft a script for automated ingestion and cataloging of Teradata data into Amazon S3
Checking the Results
Summary
Create Applications
Connect to Teradata using JDBC
Overview
Prerequisites
Create a Maven project
Add dependency to your maven project
Code to send a query
Add a test
Run the tests
Summary
Further reading
Connect to Teradata using Python
Overview
Prerequisites
Code to send a query
Summary
Further reading
Query Teradata from a Mule service
Overview
Prerequisites
Example service
Setup
Run
Further reading
Send queries using REST API
Overview
Prerequisites
Query Service API examples
Connect to your Query Service instance
HTTP Basic authentication
JWT authentication
Make a simple API request with basic options
Request a response in CSV format
Use explicit session to submit a query
Use asynchronous queries
Get a list of active or queued queries
Resources
Using Anypoint Studio to Configure Teradata Connector - Mule 4
Create a Mule Project
Add the Connector to Your Mule Project
Configure a Source
Add a Connector Operation to the Flow
Configure a Global Element for the Connector
View the App Log
See Also
Teradata Connector Reference - Mule 4
Configurations
Default Configuration
Parameters
Connection Types
Data Source Reference Connection
Parameters
Teradata Connection
Parameters
Operations
Associated Sources
Bulk Delete
Parameters
Output
For Configurations
Throws
Bulk Insert
Parameters
Output
For Configurations
Throws
Bulk Update
Parameters
Output
For Configurations
Throws
Delete
Parameters
Output
For Configurations
Throws
Execute DDL
Parameters
Output
For Configurations
Throws
Execute Script
Parameters
Output
For Configurations
Throws
Insert
Parameters
Output
For Configurations
Throws
Select
Parameters
For Configurations
Working with Pooling Profiles
Throws
Query Single
Parameters
For Configurations
Working with Pooling Profiles
Throws
Stored Procedure
Parameters
Output
For Configurations
Working with Pooling Profiles
Throws
Update
Parameters
Output
For Configurations
Throws
Sources
On Table Row
Parameters
Output
For Configurations
Types
Pooling Profile
Column Type
Reconnection
Reconnect
Reconnect Forever
Tls
Trust Store
Key Store
Standard Revocation Check
Custom Ocsp Responder
Crl File
Expiration Policy
Redelivery Policy
Parameter Type
Type Classifier
Statement Result
Repeatable In Memory Iterable
Repeatable File Store Iterable
Repeatable In Memory Stream
Output Parameter
See Also
Teradata Connector - Mule 4
Before You Begin
Common Use Cases for the Connector
Examples
See Also
Analyze Data
Use Teradata from a Jupyter notebook
Overview
Options
Teradata libraries
Teradata Jupyter Docker image
Summary
Further reading
Deploy Teradata Jupyter extensions to JupyterHub
Overview
Use Teradata Jupyter Docker image
Install Teradata Jupyter Docker image in your registry
Use Teradata Jupyter Docker image in JupyterHub
Customize Teradata Jupyter Docker image
Customize an existing Docker image to include Teradata extensions
Further reading
Train ML models in Teradata using In-Database Analytic Functions
Overview
Prerequisites
Load the sample data
Understand the sample data
Prepare the dataset
Feature engineering
TD_OneHotEncodingFit
TD_ScaleFit
TD_ColumnTransformer
Train/test split
Training with generalized linear model
Scoring on testing dataset
Model evaluation
Summary
Further reading
Run scripts on Teradata
Overview
Prerequisites
Hello World
Supported languages
Uploading scripts
Passing data stored in Teradata to SCRIPT
Inserting SCRIPT output into a table
Summary
Further reading
Perform time series analysis using Teradata
Overview
Prerequisites
Import data sets from GCS using Native Object Store (NOS)
Basic time series operations
Summary
Further reading
Use Amazon SageMaker AI with Teradata
Overview
Prerequisites
Load data
Train the model
Deploy the model
Create a model
Create an endpoint configuration
Create endpoint
Summary
Further reading
Integrate Teradata Jupyter extensions with SageMaker AI notebook instance
Overview
Prerequisites
Integration
Steps to integrate with notebook instance
Further reading
Create Visualizations in Power BI using Teradata
Overview
Prerequisites
Getting Started
Install Power BI Desktop
Install the .NET Data Provider for Teradata
Connect to Teradata
Next steps
Integrate Teradata with KNIME Analytics Platform
Overview
About KNIME Analytics Platform
Prerequisites
Integration Procedure
Summary
Further reading
Use geographic reference data with Teradata
Overview
Prerequisites
Option 1: Load a GeoJson document into Teradata
Get and load the GeoJson document
Load the GeoJson document in Teradata
Use the map from Teradata
Option 2: Prepare a GeoJson document with Python and load it into Teradata
Get and load the GeoJson document
Open the GeoJson file and type it as a dictionary
Optional Check the content of the file
Create a Teradata connection and load our file in a staging table
Create and our geography refernce table
Use your data
Summary

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