Summarize this article with:
Trusted by data-driven companies
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.
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
- 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
Move Large Volumes, Fast
An Extensible Open-Source Standard
Full Control & Security
Fully Featured & Integrated
Enterprise Support with SLAs
What our users say
Andre Exner
"For TUI Musement, Airbyte cut development time in half and enabled dynamic customer experiences."
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."
Start by logging into your Recurly account. Navigate to the data export section, which is typically available for reports and data extraction. Choose the specific data you want to export, such as customer data, transactions, or invoice details. Export this data in a CSV or JSON format, as these are commonly used formats for data transfer. Ensure that all necessary fields are included in the export for your needs.
Once you have exported the data, you should clean and prepare it. This involves checking for any missing or corrupt data, ensuring consistency in data fields, and formatting the data to match the schema in Teradata Vantage. Use data cleaning tools or scripts to standardize data formats, such as date and currency formats, ensuring they align with Teradata's requirements.
Set up a secure environment to connect to your Teradata Vantage system. This involves configuring your network and firewall settings to allow secure SSH or VPN access to the Teradata system. Ensure that your access credentials are ready and that you have permissions to upload and manage data on the Teradata Vantage platform.
Before importing data, create the necessary tables in Teradata Vantage that match the structure of your cleaned data. Use Teradata SQL Assistant or a similar tool to define tables with the appropriate data types and constraints. Ensure that the schema matches the prepared data to facilitate a smooth import process.
Use a secure file transfer protocol (such as SFTP or SCP) to move your CSV or JSON files from your local machine to the Teradata server. Ensure that files are transferred to a directory that is accessible by your Teradata import utilities. Verify that the files have been transferred correctly and that no data has been lost or corrupted during the transfer.
Utilize Teradata utilities such as FastLoad, MultiLoad, or TPT (Teradata Parallel Transporter) to import the data from the server directory into the target tables in Teradata Vantage. These tools are designed to handle large data volumes efficiently. Write and execute the appropriate scripts to perform the import, ensuring that all data mappings are correct and that the data is loaded without errors.
After loading the data, perform a thorough verification and validation process. Run queries to check that the data in Teradata Vantage matches the original data set from Recurly. Look for discrepancies, such as missing records or incorrect data types. Validate data integrity by checking constraints and performing sample checks on key data fields. Make any necessary adjustments and reload data if discrepancies are found.
This guide outlines a manual process to move data from Recurly to Teradata Vantage, ensuring data integrity and security throughout the transfer.
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.
Recurly is an SaaS subscription billing management platform that powers over 2,000 brands, including Asana, BarkBox, Cinemark, Sling TV, and Twitch. Automating the repetitive task of sending recurring bills month after month, Recurly provides management for thousands of subscription-based businesses worldwide. Recurly is quick and easy to set up and integrate into existing systems, and sales include service support so merchants can get help as needed. Recurly is a powerful tool that reduces subscriber churn and increases business revenue.
Recurly's API provides access to a wide range of data related to subscription management and billing. The following are the categories of data that Recurly's API gives access to:
1. Accounts: Information about customer accounts, including contact details, billing information, and subscription status.
2. Subscriptions: Details about active and inactive subscriptions, including plan information, billing cycles, and renewal dates.
3. Transactions: Information about all transactions related to a customer's account, including payments, refunds, and credits.
4. Invoices: Details about all invoices generated for a customer's account, including invoice items, due dates, and payment status.
5. Plans: Information about the different subscription plans offered by a business, including pricing, features, and billing intervals.
6. Add-ons: Details about additional products or services that can be added to a subscription, including pricing and billing intervals.
7. Coupons: Information about discounts or promotions offered to customers, including coupon codes, expiration dates, and usage limits.
8. Metrics: Data related to subscription and revenue metrics, including churn rate, customer lifetime value, and monthly recurring revenue.
Overall, Recurly's API provides businesses with a comprehensive set of data to manage their subscription-based business models effectively.
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.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
