How to load data from BigQuery to TiDB

Learn how to use Airbyte to synchronize your BigQuery data into TiDB within minutes.

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Set up a BigQuery connector in Airbyte

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

Set up TiDB for your extracted BigQuery data

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

Configure the BigQuery 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.

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TL;DR

set up BigQuery as a source connector (using Auth, or usually an API key)
set up TiDB 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 BigQuery

BigQuery is a cloud-based data warehousing and analytics platform that allows users to store, manage, and analyze large amounts of data in real-time. It is a fully managed service that eliminates the need for users to manage their own infrastructure, and it offers a range of features such as SQL querying, machine learning, and data visualization. BigQuery is designed to handle petabyte-scale datasets and can be used for a variety of use cases, including business intelligence, data exploration, and predictive analytics. It is a powerful tool for organizations looking to gain insights from their data and make data-driven decisions.

What is TiDB

TiDB is a distributed SQL database that is designed to handle large-scale online transaction processing (OLTP) and online analytical processing (OLAP) workloads. It is an open-source, cloud-native database that is built to be highly available, scalable, and fault-tolerant. TiDB uses a distributed architecture that allows it to scale horizontally across multiple nodes, while also providing strong consistency guarantees. It supports SQL and offers compatibility with MySQL, which makes it easy for developers to migrate their existing applications to TiDB. TiDB is used by companies such as Didi Chuxing, Mobike, and Meituan-Dianping to power their mission-critical applications.

Integrate BigQuery with TiDB in minutes

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Prerequisites

A BigQuery account to transfer your customer data automatically from.
A TiDB 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 BigQuery and TiDB, for seamless data migration.

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

Step 1: Set up BigQuery as a source connector

1. First, you need to have a Google Cloud Platform account and a project with BigQuery enabled.

2. Go to the Google Cloud Console and create a new service account with the necessary permissions to access your BigQuery data.

3. Download the JSON key file for the service account and keep it safe.

4. Open Airbyte and go to the Sources page.

5. Click on the "Create a new source" button and select "BigQuery" from the list of available sources.

6. Enter a name for your source and click on "Next".

7. In the "Connection Configuration" section, enter the following information:
- Project ID: the ID of your Google Cloud Platform project
- JSON Key: copy and paste the contents of the JSON key file you downloaded earlier
- Dataset: the name of the dataset you want to connect to

8. Click on "Test Connection" to make sure everything is working correctly.

9. If the test is successful, click on "Create Source" to save your configuration.

10. You can now use your BigQuery source connector to extract data from your dataset and load it into Airbyte for further processing.

Step 2: Set up TiDB as a destination connector

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.
3. Scroll down until you find the TiDB destination connector and click on it.
4. You will be prompted to enter your TiDB database credentials, including the host, port, username, and password.
5. Once you have entered 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 TiDB destination connector settings.
7. You can now use the TiDB destination connector to transfer data from your source connectors to your TiDB database.
8. To set up a data integration pipeline, navigate to the "Connections" tab on the left-hand side of the screen and create a new connection.
9. Select your TiDB destination connector as the destination and choose your source connector as the source.
10. Configure the settings for your data integration pipeline, including the frequency of data transfers and any data transformations that you want to apply.
11. Once you have configured your data integration pipeline, click on the "Save" button to save your settings.
12. Your data integration pipeline will now run automatically, transferring data from your source connectors to your TiDB database on a regular basis.

Step 3: Set up a connection to sync your BigQuery data to TiDB

Once you've successfully connected BigQuery as a data source and TiDB 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 BigQuery from the dropdown list of your configured sources.
Select your destination: Choose TiDB 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 BigQuery objects you want to import data from towards TiDB. 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 BigQuery to TiDB according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your TiDB data warehouse is always up-to-date with your BigQuery data.

Use Cases to transfer your BigQuery data to TiDB

Integrating data from BigQuery to TiDB provides several benefits. Here are a few use cases:

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

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a BigQuery account as an Airbyte data source connector.
Configure TiDB as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from BigQuery to TiDB 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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Sync with Airbyte

Step 1: Set up BigQuery as a source connector

1. First, you need to have a Google Cloud Platform account and a project with BigQuery enabled.

2. Go to the Google Cloud Console and create a new service account with the necessary permissions to access your BigQuery data.

3. Download the JSON key file for the service account and keep it safe.

4. Open Airbyte and go to the Sources page.

5. Click on the "Create a new source" button and select "BigQuery" from the list of available sources.

6. Enter a name for your source and click on "Next".

8. Click on "Test Connection" to make sure everything is working correctly.

9. If the test is successful, click on "Create Source" to save your configuration.

10. You can now use your BigQuery source connector to extract data from your dataset and load it into Airbyte for further processing.

Step 2: Set up TiDB as a destination connector

Step 3: Set up a connection to sync your BigQuery data to TiDB

Once you've successfully connected BigQuery as a data source and TiDB 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 BigQuery from the dropdown list of your configured sources.
Select your destination: Choose TiDB 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 BigQuery objects you want to import data from towards TiDB. 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 BigQuery to TiDB according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your TiDB data warehouse is always up-to-date with your BigQuery data.

How to Sync BigQuery to TiDB Manually

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Step 8:

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 BigQuery?

What data can you extract from BigQuery?

BigQuery 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 data types, such as CSV, JSON, and Avro files.
2. Semi-structured data: This includes data that has some structure, but not necessarily a fixed schema, such as XML and JSON files.
3. Unstructured data: This includes data that has no predefined structure, such as text, images, and videos.
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 spatial databases.
6. Machine learning data: This includes data that is used to train machine learning models, such as labeled datasets and feature vectors.
7. Streaming data: This includes data that is generated in real-time, such as social media feeds, IoT sensor data, and log files.

Overall, BigQuery's API provides access to a wide range of data types, making it a powerful tool for data analysis and machine learning.

How do I transfer data from BigQuery?

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 BigQuery to TiDB 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 BigQuery to TiDB 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.

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Databases

Warehouses and Lakes

How to load data from BigQuery to TiDB

Learn how to use Airbyte to synchronize your BigQuery data into TiDB within minutes.

Try Airbyte Cloud free

Deploy Airbyte Open Source

Step 1: Setup BigQuery

Step 2: Setup TiDB

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between BigQuery and TiDB

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up BigQuery as a source connector (using Auth, or usually an API key)
set up TiDB 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 BigQuery