How to load data from Teradata source to Postgres destination

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

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Set up a Teradata source connector in Airbyte

Connect to Teradata source or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Postgres destination for your extracted Teradata source data

Select Postgres destination where you want to import data from your Teradata source source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Teradata source to Postgres destination in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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TL;DR

set up Teradata source as a source connector (using Auth, or usually an API key)
set up Postgres destination as a destination connector
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 Teradata source

Teradata is a data management and analytics platform that helps businesses to collect, store, and analyze large amounts of data. It provides a range of tools and services that enable organizations to make data-driven decisions and gain insights into their operations. Teradata's platform is designed to handle complex data sets and support advanced analytics, including machine learning and artificial intelligence. It also offers cloud-based solutions that allow businesses to scale their data management and analytics capabilities as needed. Overall, Teradata helps businesses to unlock the value of their data and drive better outcomes across their operations.

What is Postgres destination

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 web, mobile, and analytics applications use PostgreSQL as the primary data warehouse or data store.

Integrate Teradata source with Postgres destination in minutes

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Prerequisites

A Teradata source account to transfer your customer data automatically from.
A Postgres destination account.
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 Teradata source and Postgres destination, for seamless data migration.

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

Step 1: Set up Teradata source as a source connector

1. First, navigate to the Airbyte website and create an account.
2. Once you have logged in, click on the ""Sources"" tab on the left-hand side of the screen.
3. Scroll down until you find the Teradata source connector and click on it.
4. You will be prompted to enter your Teradata database credentials, including the host, port, username, and password.
5. After entering your credentials, click on the ""Test"" button to ensure that the connection is successful.
6. If the test is successful, click on the ""Save"" button to save your Teradata source connector settings.
7. You can now use the Teradata source connector to extract data from your Teradata database and load it into your destination of choice.
8. To set up a destination connector, navigate to the ""Destinations"" tab on the left-hand side of the screen and select the destination you want to use.
9. Follow the prompts to enter your destination credentials and configure your destination settings.
10. Once you have set up both your source and destination connectors, you can create a new pipeline to move data from your Teradata database to your destination.

Step 2: Set up Postgres destination as a destination connector

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

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

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Teradata source from the dropdown list of your configured sources.
Select your destination: Choose Postgres destination from the dropdown list of your configured destinations.
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.
Select the data to sync: Choose the specific Teradata source objects you want to import data from towards Postgres destination. You can sync all data or select specific tables and fields.
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.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Teradata source to Postgres destination according to your settings.

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

Use Cases to transfer your Teradata source data to Postgres destination

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

Advanced Analytics: Postgres destination’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Teradata source data, extracting insights that wouldn't be possible within Teradata source alone.
Data Consolidation: If you're using multiple other sources along with Teradata source, syncing to Postgres destination 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.
Historical Data Analysis: Teradata source has limits on historical data. Syncing data to Postgres destination allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Postgres destination provides robust data security features. Syncing Teradata source data to Postgres destination ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Postgres destination can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Teradata source data.
Data Science and Machine Learning: By having Teradata source data in Postgres destination, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Teradata source provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Postgres destination, providing more advanced business intelligence options. If you have a Teradata source table that needs to be converted to a Postgres destination table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a Teradata source account as an Airbyte data source connector.
Configure Postgres destination as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Teradata source to Postgres destination 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!

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How to Sync Teradata source to Postgres destination Manually

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FAQs

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What is Teradata source?

What data can you extract from Teradata source?

Teradata's API provides access to a wide range of data types, including:

1. Structured data: This includes data that is organized into tables with defined columns and rows, such as customer information, sales data, and financial records.

2. Unstructured data: This includes data that is not organized in a predefined manner, such as social media posts, emails, and documents.

3. Semi-structured data: This includes data that has some structure, but not as much as structured data. Examples include XML files and JSON data.

4. Time-series data: This includes data that is organized by time, such as stock prices, weather data, and sensor readings.

5. Geospatial data: This includes data that is related to geographic locations, such as maps, GPS coordinates, and location-based services.

6. Machine-generated data: This includes data that is generated by machines, such as log files, sensor data, and telemetry data.

Overall, Teradata's API provides access to a wide range of data types, allowing developers and data analysts to work with diverse data sets and extract insights from them.

How do I transfer data from Teradata source?

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 Teradata to PostgreSQL as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Teradata to PostgreSQL and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

Back to all tutorials

Databases

Warehouses and Lakes

How to load data from Teradata source to Postgres destination

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

Try Airbyte Cloud free

Deploy Airbyte Open Source

TL;DR

What is Teradata source

What is Postgres destination

Prerequisites

Step 1: Setup Teradata source

Step 2: Setup Postgres destination

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Teradata source and Postgres destination

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up Teradata source as a source connector (using Auth, or usually an API key)
set up Postgres destination as a destination connector
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 Teradata source

What is Postgres destination

Integrate Teradata source with Postgres destination in minutes

Try for free now

Prerequisites

A Teradata source account to transfer your customer data automatically from.
A Postgres destination account.
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.

Step 1: Set up Teradata source as a source connector

Step 2: Set up Postgres destination as a destination connector

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

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

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Teradata source from the dropdown list of your configured sources.
Select your destination: Choose Postgres destination from the dropdown list of your configured destinations.
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.
Select the data to sync: Choose the specific Teradata source objects you want to import data from towards Postgres destination. You can sync all data or select specific tables and fields.
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.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Teradata source to Postgres destination according to your settings.

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

Use Cases to transfer your Teradata source data to Postgres destination

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

Advanced Analytics: Postgres destination’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Teradata source data, extracting insights that wouldn't be possible within Teradata source alone.
Data Consolidation: If you're using multiple other sources along with Teradata source, syncing to Postgres destination 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.
Historical Data Analysis: Teradata source has limits on historical data. Syncing data to Postgres destination allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Postgres destination provides robust data security features. Syncing Teradata source data to Postgres destination ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Postgres destination can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Teradata source data.
Data Science and Machine Learning: By having Teradata source data in Postgres destination, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Teradata source provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Postgres destination, providing more advanced business intelligence options. If you have a Teradata source table that needs to be converted to a Postgres destination table, Airbyte can do that automatically.