How to load data from SFTP Bulk to Teradata
Learn how to use Airbyte to synchronize your SFTP Bulk data into Teradata within minutes.
Building your pipeline or Using Airbyte
Airbyte is the only open source solution empowering data teams to meet all their growing custom business demands in the new AI era.
Building in-house pipelines
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
After Airbyte
- Reliable and accurate
- Extensible and scalable for all your needs
- Deployed and governed your way
Start syncing with Airbyte in 3 easy steps within 10 minutes
Take a virtual tour
Demo video of Airbyte Cloud
Demo video of AI Connector Builder
Setup Complexities simplified!
Simple & Easy to use Interface
Airbyte is built to get out of your way. Our clean, modern interface walks you through setup, so you can go from zero to sync in minutes—without deep technical expertise.
Guided Tour: Assisting you in building connections
Whether you’re setting up your first connection or managing complex syncs, Airbyte’s UI and documentation help you move with confidence. No guesswork. Just clarity.
Airbyte AI Assistant that will act as your sidekick in building your data pipelines in Minutes
Airbyte’s built-in assistant helps you choose sources, set destinations, and configure syncs quickly. It’s like having a data engineer on call—without the overhead.
What sets Airbyte Apart
Modern GenAI Workflows
Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.
Move Large Volumes, Fast
Quickly get up and running with a 5-minute setup that enables both incremental and full refreshes for databases of any size, seamlessly scaling to handle large data volumes. Our optimized architecture overcomes performance bottlenecks, ensuring efficient data synchronization even as your datasets grow from gigabytes to petabytes.
An Extensible Open-Source Standard
More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s AI Connector Builder lets you edit or add new connectors in minutes.
Full Control & Security
Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.
Fully Featured & Integrated
Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.
Enterprise Support with SLAs
Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.
What our users say
Raman Singh
Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend
Chase Zieman
“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”
Rupak Patel
"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."
How to Sync to Manually
Step 1: Set Up SFTP Connection
Begin by establishing a secure connection to the SFTP server. Use command-line tools such as `sftp` or `scp` to log in to the server. You will need credentials such as the server address, username, password, or an SSH key. For instance, open a terminal and use a command like `sftp username@hostname` to connect.
Step 2: Navigate to the Data Directory
Once connected to the SFTP server, navigate to the directory containing the bulk data files. Use `cd` commands within the SFTP prompt to change directories. For example, use `cd /path/to/data/files` to move to the correct folder.
Step 3: Download Data Files
Use the `get` command to download the data files from the SFTP server to your local machine. If you need multiple files, you can use wildcard characters, like `get *.csv` to download all CSV files in the directory. Ensure you have sufficient disk space on your local machine for the data.
Step 4: Prepare Data for Teradata Import
Ensure the downloaded data files are formatted correctly for Teradata. This may involve converting file formats (e.g., from CSV to another supported format) or cleaning the data to remove any inconsistencies or errors. Use tools like `awk`, `sed`, or a scripting language like Python to preprocess the data.
Step 5: Create Teradata Table Structure
Before importing data, create the necessary table structure in Teradata to accommodate the data. Use Teradata SQL Assistant or BTEQ (Basic Teradata Query) to define the table schema. An example SQL command might be:
```sql
CREATE TABLE my_table (
column1 INTEGER,
column2 VARCHAR(50),
column3 DATE
);
```
Step 6: Load Data into Teradata Using BTEQ
Use BTEQ to load the data files into Teradata. Write a BTEQ script that uses the `.IMPORT` and `.RUN FILE` commands to read data from the local files and insert it into the Teradata tables. An example BTEQ script might look like:
```plaintext
.LOGON my_teradata_server/username,password;
.IMPORT INFILE 'local_data_file.csv' FORMAT VARTEXT ',';
.REPEAT *;
USING (column1 INTEGER, column2 VARCHAR(50), column3 DATE)
INSERT INTO my_table (column1, column2, column3)
VALUES (:column1, :column2, :column3);
.LOGOFF;
```
Step 7: Verify Data Import
After the data import process is complete, verify the data in Teradata to ensure it matches the source files. Run SQL queries to compare row counts and sample the data for accuracy. This can be done using:
```sql
SELECT COUNT(*) FROM my_table;
SELECT * FROM my_table SAMPLE 10;
```
Check for any discrepancies and address them by reviewing the data preprocessing steps or the import script.