Warehouses and Lakes
Databases

How to load data from Postgres to Teradata

Learn how to use Airbyte to synchronize your Postgres data into Teradata within minutes.

TL;DR

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:

  1. set up Postgres as a source connector (using Auth, or usually an API key)
  2. set up Teradata as a destination connector
  3. define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Postgres

An object-relational database management system, PostgreSQL is able to handle a wide range of workloads, supports multiple standards, and is cross-platform, running on numerous operating systems including Microsoft Windows, Solaris, Linux, and FreeBSD. It is highly extensible, and supports more than 12 procedural languages, Spatial data support, Gin and GIST Indexes, and more. Many webs, mobile, and analytics applications use PostgreSQL as the primary data warehouse or data store.

What is Teradata

Teradata is a multi-cloud data platform for enterprise analytics companies that provides solutions for business challenges from beginning to end. With Teradata, you have the ability to manage large and varied data workloads now and in the future. The company offers data platforms, applications, and services for data warehousing and analytics.

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Prerequisites

  1. A Postgres account to transfer your customer data automatically from.
  2. A Teradata account.
  3. An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Postgres and Teradata, for seamless data migration.

When using Airbyte to move data from Postgres to Teradata, it extracts data from Postgres using the source connector, converts it into a format Teradata can ingest using the provided schema, and then loads it into Teradata via the destination connector. This allows businesses to leverage their Postgres data for advanced analytics and insights within Teradata, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Postgres as a source connector

1. Open your PostgreSQL database and create a new user with the necessary permissions to access the data you want to replicate.

2. Obtain the hostname or IP address of your PostgreSQL server and the port number it is listening on.

3. Create a new database in PostgreSQL that will be used to store the replicated data.

4. Obtain the name of the database you just created.

5. In Airbyte, navigate to the PostgreSQL source connector and click on "Create Connection".

6. Enter a name for your connection and fill in the required fields, including the hostname or IP address, port number, database name, username, and password.

7. Test the connection to ensure that Airbyte can successfully connect to your PostgreSQL database.

8. Select the tables or views you want to replicate and configure any necessary settings, such as the replication frequency and the replication method.

9. Save your configuration and start the replication process.

10. Monitor the replication process to ensure that it is running smoothly and troubleshoot any issues that arise.

Step 2: Set up Teradata as a destination connector

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.
3. Scroll down until you find the Teradata destination connector and click on it.
4. You will be prompted to enter your Teradata database credentials, including the host, port, username, and password.
5. Once you have entered your credentials, click on the "Test Connection" button to ensure that Airbyte can successfully connect to your Teradata database.
6. If the connection is successful, click on the "Save" button to save your Teradata destination connector settings.
7. You can now create a new pipeline in Airbyte and select Teradata as your destination connector.
8. Follow the prompts to configure your pipeline and map your source data to your Teradata database.
9. Once your pipeline is configured, you can run it to start transferring data from your source to your Teradata database.

Step 3: Set up a connection to sync your Postgres data to Teradata

Once you've successfully connected Postgres as a data source and Teradata as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

  1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
  2. Choose your source: Select Postgres from the dropdown list of your configured sources.
  3. Select your destination: Choose Teradata from the dropdown list of your configured destinations.
  4. Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
  5. Select the data to sync: Choose the specific Postgres objects you want to import data from towards Teradata. You can sync all data or select specific tables and fields.
  6. Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
  7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
  8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Postgres to Teradata according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Teradata data warehouse is always up-to-date with your Postgres data.

Use Cases to transfer your Postgres data to Teradata

Integrating data from Postgres to Teradata provides several benefits. Here are a few use cases:

  1. Advanced Analytics: Teradata’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Postgres data, extracting insights that wouldn't be possible within Postgres alone.
  2. Data Consolidation: If you're using multiple other sources along with Postgres, syncing to Teradata allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
  3. Historical Data Analysis: Postgres has limits on historical data. Syncing data to Teradata allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: Teradata provides robust data security features. Syncing Postgres data to Teradata ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: Teradata can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Postgres data.
  6. Data Science and Machine Learning: By having Postgres data in Teradata, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While Postgres provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Teradata, providing more advanced business intelligence options. If you have a Postgres table that needs to be converted to a Teradata table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a Postgres account as an Airbyte data source connector.
  2. Configure Teradata as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from Postgres to Teradata after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

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Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
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Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
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Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
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Connectors Used

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

Connectors Used

Frequently Asked Questions

What data can you extract from Postgres?

PostgreSQL gives access to a wide range of data types, including:  

1. Numeric data types: This includes integers, floating-point numbers, and decimal numbers.  

2. Character data types: This includes strings, text, and character arrays.  

3. Date and time data types: This includes dates, times, and timestamps.  

4. Boolean data types: This includes true/false values.  

5. Network address data types: This includes IP addresses and MAC addresses.  

6. Geometric data types: This includes points, lines, and polygons.  

7. Array data types: This includes arrays of any of the above data types.  

8. JSON and JSONB data types: This includes JSON objects and arrays.  

9. XML data types: This includes XML documents.  

10. Composite data types: This includes user-defined data types that can contain multiple fields of different data types.  

Overall, PostgreSQL's API provides access to a wide range of data types, making it a versatile and powerful tool for data management and analysis.

What data can you transfer to Teradata?

You can transfer a wide variety of data to Teradata. This usually includes structured, semi-structured, and unstructured data like transaction records, log files, JSON data, CSV files, and more, allowing robust, scalable data integration and analysis.

What are top ETL tools to transfer data from Postgres to Teradata?

The most prominent ETL tools to transfer data from Postgres to Teradata include:

  • Airbyte
  • Fivetran
  • Stitch
  • Matillion
  • Talend Data Integration

These tools help in extracting data from Postgres and various sources (APIs, databases, and more), transforming it efficiently, and loading it into Teradata and other databases, data warehouses and data lakes, enhancing data management capabilities.