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Sync data from Airtable to PostgreSQL
CloudQuery is the simple, fast data integration platform that can replicate your data from Airtable to PostgreSQL
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Step by step guide for how to export data from Airtable to PostgreSQL
Table of Contents
MacOS Setup
Step 1: Install CloudQuery
To install CloudQuery, run the following command in your terminal:
brew install cloudquery/tap/cloudqueryStep 2: Create a Configuration File
Next, run the following command to initialize a sync configuration file for Airtable to PostgreSQL:
cloudquery init --source=airtable --destination=postgresqlThis will generate a config file named airtable_to_postgresql.yaml. Follow the instructions to fill out the necessary fields to authenticate against your own environment.
Step 3: Log in to CloudQuery CLI
Next, log in to the CloudQuery CLI. If you have't already, you can sign up for a free account as part of this step:
cloudquery loginStep 4: Run a Sync
cloudquery sync airtable_to_postgresql.yamlThis will start syncing data from the Airtable database to your PostgreSQL database! 🚀
See the CloudQuery documentation portal for more deployment guides, options and further tips.
FAQs
What is CloudQuery?
CloudQuery is an open-source tool that helps you extract, transform, and load cloud asset data from various sources into databases for security, compliance, and visibility.
Why does CloudQuery require login?
Logging in allows CloudQuery to authenticate your access to the CloudQuery Hub and monitor usage for billing purposes. Data synced with CloudQuery remains private to your environment and is not shared with our servers or any third parties.
What data does CloudQuery have access to?
CloudQuery accesses only the metadata and configurations of your cloud resources that you specify without touching sensitive data or workloads.
How is CloudQuery priced?
CloudQuery offers flexible pricing based on the number of cloud accounts and usage. Visit our pricing page for detailed plans.
Is there a free version of CloudQuery?
Yes, CloudQuery offers a free plan that includes basic features, perfect for smaller teams or personal use. More details can be found on our pricing page.
How do I authenticate the Airtable source integration?
In order to use CloudQuery with your Airtable data and sync it to PostgreSQL, you’ll need to create a personal access token for the Airtable API. Full details on how to do this can be found on the Airtable website.
How does the Airtable API work?
Airtable provides customised API documentation for each of your bases. To find out more about how the API interacts with any particular Airtable base and the data that you will be able to sync to PostgreSQL, log in to Airtable and navigate to this page to view your customized documentation.
Which Airtable fields can I sync to PostgreSQL?
Airtable’s customised API documentation provides a list of fields that can be synced from any particular base and the details that you will need to set up a sync from Airtable to PostgreSQL. Simply sign in to your Airtable account and visit this page to review the details.
How long will it take to sync my data from Airtable to PostgreSQL?
Airtable’s API is limited to a maximum of 5 requests per second. This is the primary limitation to the speed of any sync from Airtable to PostgreSQL.
Which database versions are supported?
The CloudQuery PostgreSQL integration supports syncing to PostgreSQL version 10 or higher and CockroachDB version 20.2 or higher.
How long will the sync take?
Sync duration depends on several factors, but there are a number of CloudQuery features that ensure that syncs are as fast as possible. CloudQuery syncs data from Airtable to PostgreSQL in a streaming fashion using Apache Arrow. This means that as soon as it receives data from Airtable it delivers it to the PostgreSQL integration. This means that data is delivered as the sync progresses rather than only at the end.
Can I send data to multiple PostgreSQL instances using the destination plug-in?
Yes, you can configure multiple destination blocks for different PostgreSQL instances or databases.
What are the best practices for handling large datasets with the PostgreSQL destination integration?
Use indexing, partitioning, and batch inserts to manage large datasets effectively and minimize performance impacts.
How do I monitor and troubleshoot data transfers to PostgreSQL?
Check CloudQuery logs for detailed error messages, validate connectivity settings, and monitor database performance using PostgreSQL’s built-in tools.