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."
Begin by exporting your data from Notion. Open the Notion page or database you want to export, click on the three dots in the top-right corner, and select "Export." Choose the format that best suits your needs, such as CSV for tables or Markdown/HTML for text content. Download the exported file to your local machine.
If your Notion data was exported as a CSV, open it using a spreadsheet program like Excel or Google Sheets. Check for any inconsistencies, such as missing headers or incorrect data types, and make necessary corrections. Ensure that the CSV structure aligns with the schema you plan to use in TiDB.
Install and set up TiDB on your local machine or server if it is not already running. Follow the official [TiDB documentation](https://docs.pingcap.com/tidb/stable) for installation instructions. Ensure that your TiDB cluster is up and running, and you have access to the necessary credentials for database creation and data import.
Access your TiDB server using a MySQL client or command-line interface. Execute SQL commands to create a new database and tables that will store your Notion data. Make sure the table schema matches the structure of your CSV files. For example:
```sql
CREATE DATABASE notion_data;
USE notion_data;
CREATE TABLE example_table (
id INT PRIMARY KEY,
name VARCHAR(255),
description TEXT
);
```
Write a script or use command-line tools to import your CSV data into TiDB. You can use the `LOAD DATA` SQL command to import data efficiently. For instance:
```sql
LOAD DATA LOCAL INFILE '/path/to/your/file.csv'
INTO TABLE example_table
FIELDS TERMINATED BY ','
ENCLOSED BY '"'
LINES TERMINATED BY '\n'
IGNORE 1 ROWS; -- Adjust depending on the presence of a header row
```
Run the script or execute the `LOAD DATA` command to import your data into TiDB. Make sure you handle any errors or warnings that may occur during the import process. Verify that all data has been imported correctly by running a few `SELECT` queries on your TiDB tables.
After the import, verify the integrity of your data. Check for any discrepancies or missing entries by comparing the TiDB table content with your original Notion data. Once confirmed, clean up any temporary files or scripts used during the process. Ensure that your TiDB database is performing as expected with the new data.
Following these steps will allow you to manually move data from Notion to TiDB without relying on third-party connectors or integrations.
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.
Notion is an all-in-one workspace that allows users to organize their personal and professional lives in one place. It combines features of note-taking apps, project management tools, and databases to create a customizable and flexible platform. Users can create pages, databases, and boards to manage tasks, projects, and information. Notion also offers a variety of templates and integrations with other apps to enhance productivity. Its user-friendly interface and collaborative features make it a popular choice for individuals and teams looking to streamline their workflows and stay organized.
Notion's API provides access to a wide range of data types, including:
1. Pages: This includes all the pages in a Notion workspace, including their properties and content.
2. Databases: Notion's databases are a powerful way to organize and manage data. The API provides access to all the databases in a workspace, including their properties and content.
3. Blocks: Notion's blocks are the building blocks of pages and databases. The API provides access to all the blocks in a workspace, including their content and properties.
4. Users: Notion's API provides access to information about the users in a workspace, including their name, email address, and profile picture.
5. Workspaces: The API provides access to information about the workspaces themselves, including their name and ID.
6. Integrations: Notion's API allows developers to create integrations with other tools and services, such as Slack or Zapier.
Overall, Notion's API provides a comprehensive set of tools for accessing and manipulating data within a workspace, making it a powerful platform for building custom applications and workflows.
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:
