How to load data from PartnerStack to TiDB

Learn how to use Airbyte to synchronize your PartnerStack data into TiDB 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

Bespoke pipelines are:
  • Inconsistent and inaccurate data
  • Laborious and expensive
  • Brittle and inflexible
Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.

After Airbyte

Airbyte connections are:
  • Reliable and accurate
  • Extensible and scalable for all your needs
  • Deployed and governed your way
All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and AI Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a PartnerStack connector in Airbyte

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

Set up TiDB for your extracted PartnerStack data

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

Configure the PartnerStack to TiDB 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.

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

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Setup Complexities simplified!

You don’t need to put hours into figuring out how to use Airbyte to achieve your Data Engineering goals.

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.

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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.

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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

Tech Lead at Symend

Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend

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Chase Zieman

Chief Data Officer

“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.”

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Rupak Patel

Operational Intelligence Manager

"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."

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How to Sync to Manually

Step 1: Understand Data Structures

Begin by familiarizing yourself with the data structures in both PartnerStack and TiDB. Identify the types of data you want to move, such as user data, transactions, or partner information. Ensure that you understand the format and schema used by PartnerStack and how it translates to TiDB's requirements.

Step 2: Extract Data from PartnerStack

Use the PartnerStack API to extract the necessary data. You can do this by writing scripts in a programming language like Python or JavaScript to send HTTP requests to the API endpoints that provide the data you need. Make sure to handle authentication properly and paginate through results if necessary.

Step 3: Transform Data to TiDB Format

Once you have the data extracted, transform it into a format compatible with TiDB. This may involve converting data types, normalizing data, and preparing CSV or SQL files. Write scripts to automate the transformation process, ensuring that the data adheres to the schema and constraints of your TiDB database.

Step 4: Prepare TiDB Database

Set up your TiDB database environment, ensuring that it is ready to receive the data. This involves creating the necessary tables and defining the schema according to your transformed data. Use SQL commands to create tables, set data types, and define primary keys and indexes as needed.

Step 5: Load Data into TiDB

Use TiDB's native tools to load the transformed data into your database. You can utilize the `LOAD DATA` SQL command for bulk inserts from CSV files, or write scripts to insert records individually using SQL `INSERT` statements if you are working with smaller datasets.

Step 6: Verify Data Integrity

After loading the data, perform checks to ensure that it has been accurately and completely transferred. Run SQL queries to count records, validate data types, and check for any discrepancies between the data in PartnerStack and TiDB. This step helps catch any issues early before the data is used in production.

Step 7: Automate and Schedule Future Transfers

If you need to regularly update the data in TiDB, automate the extraction, transformation, and loading process. Write scripts to schedule these tasks using cron jobs or similar scheduling tools on your server. This ensures that your TiDB database stays up-to-date with the latest data from PartnerStack without manual intervention.

By following these steps, you can successfully move data from PartnerStack to TiDB without relying on third-party connectors or integrations.