How to load data from SpaceX API to BigQuery

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

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Set up a SpaceX API connector in Airbyte

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

Set up BigQuery for your extracted SpaceX API data

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

Configure the SpaceX API to BigQuery 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 SpaceX API as a source connector (using Auth, or usually an API key)
set up BigQuery 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 SpaceX API

SpaceX manufactures, designs and launches advanced rockets and spacecraft. SpaceX has successfully launched 11 Falcon 9 carrier rockets this year, remaining two more launches already planned. SpaceX is developing a low latency, broadband internet system to meet the needs. SpaceX API provides real-time SpaceX satellite tracking data. SpaceX provides two-way satellite-based internet service (“Services”), receivable with a Starlink dish, Wi-Fi router, power supply and mounts ("Starlink Kit” or “Kit”).

What is BigQuery

BigQuery is an enterprise data warehouse that draws on the processing power of Google Cloud Storage to enable fast processing of SQL queries through massive datasets. BigQuery helps businesses select the most appropriate software provider to assemble their data, based on the platforms the business uses. Once a business’ data is acculumated, it is moved into BigQuery. The company controls access to the data, but BigQuery stores and processes it for greater speed and convenience.

Integrate SpaceX API with BigQuery in minutes

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Prerequisites

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

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

Step 1: Set up SpaceX API as a source connector

1. First, navigate to the Airbyte dashboard and click on "Sources" on the left-hand side of the screen.
2. Click on the "Create a new source" button and select "SpaceX API" from the list of available connectors.
3. Enter a name for your connector and click "Next".
4. Enter your SpaceX API credentials, including your API key and any other required information.
5. Test your connection to ensure that your credentials are correct and that Airbyte can successfully connect to the SpaceX API.
6. Once your connection is successful, select the data you want to replicate from the SpaceX API and configure any additional settings or filters as needed.
7. Click "Create Source" to save your configuration and begin replicating data from the SpaceX API to your destination.

Step 2: Set up BigQuery as a destination connector

1. First, navigate to the Airbyte dashboard and select the "Destinations" tab on the left-hand side of the screen.

2. Scroll down until you find the "BigQuery" destination connector and click on it.

3. Click the "Create Destination" button to begin setting up your BigQuery destination.

4. Enter your Google Cloud Platform project ID and service account credentials in the appropriate fields.

5. Next, select the dataset you want to use for your destination and enter the table prefix you want to use.

6. Choose the schema mapping for your data, which will determine how your data is organized in BigQuery.

7. Finally, review your settings and click the "Create Destination" button to complete the setup process.

8. Once your destination is created, you can begin configuring your source connectors to start syncing data to BigQuery.

9. To do this, navigate to the "Sources" tab on the left-hand side of the screen and select the source connector you want to use.

10. Follow the prompts to enter your source credentials and configure your sync settings.

11. When you reach the "Destination" step, select your BigQuery destination from the dropdown menu and choose the dataset and table prefix you want to use.

12. Review your settings and click the "Create Connection" button to start syncing data from your source to your BigQuery destination.

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

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

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

Use Cases to transfer your SpaceX API data to BigQuery

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

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

Wrapping Up

To summarize, this tutorial has shown you how to:

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