How to load data from Convex dev to DuckDB

Learn how to use Airbyte to synchronize your Convex dev data into DuckDB within minutes.

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Set up a Convex dev connector in Airbyte

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

Set up DuckDB for your extracted Convex dev data

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

Configure the Convex dev to DuckDB 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 Convex dev as a source connector (using Auth, or usually an API key)
set up DuckDB 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 Convex dev

Convex is a server less infrastructure company that has built the worldwide state management platform for web developers. Our mission is to basically change how software is formed on the Internet and who gets to form it. We aim to empower teams, large or small, to build fast, reliable, and dependable dynamic systems at scale. Convex has a great vision for the future so that developers can focus on building application code and leverage that remove the need for thinking about storage, execution, sync, queuing, or workflow.

What is DuckDB

DuckDB is an in-process SQL OLAP database management system. It has strong support for SQL. DuckDB is borrowing the SQLite shell implementation. Each database is a single file on disk. It’s analogous to “ SQLite for analytical (OLAP) workloads” (direct comparison on the SQLite vs DuckDB paper here), whereas SQLite is for OLTP ones. But it can handle vast amounts of data locally. It’s the smaller, lighter version of Apache Druid and other OLAP technologies.

Integrate Convex dev with DuckDB in minutes

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Prerequisites

A Convex dev account to transfer your customer data automatically from.
A DuckDB 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 Convex dev and DuckDB, for seamless data migration.

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

Step 1: Set up Convex dev as a source connector

1. First, navigate to the Convex.dev website and log in to your account.
2. Once logged in, click on the "Sources" tab on the left-hand side of the screen.
3. Scroll down until you find the "Airbyte" source connector and click on it.
4. You will be prompted to enter your Airbyte API URL, username, and password. Enter this information and click "Test Connection" to ensure that the credentials are correct.
5. If the connection is successful, click "Save" to add the Airbyte source connector to your list of sources in Convex.dev.
6. Next, navigate to your Airbyte dashboard and click on "Connections" on the left-hand side of the screen.
7. Click "New Connection" and select the Convex.dev source connector from the list of available sources.
8. Enter any necessary configuration details for the connection, such as the source schema and table names.
9. Once the configuration is complete, click "Create Connection" to establish the connection between Airbyte and Convex.dev.
10. You can now use the data from your Airbyte sources in Convex.dev for analysis and visualization.

Step 2: Set up DuckDB as a destination connector

1. Open the Airbyte platform and navigate to the "Destinations" tab on the left-hand side of the screen.
2. Click on the "Add Destination" button located in the top right corner of the screen.
3. Scroll down the list of available destinations until you find "DuckDB" and click on it.
4. Fill in the required information for your DuckDB database, including the host, port, database name, username, and password.
5. Test the connection to ensure that the information you provided is correct and that Airbyte can successfully connect to your DuckDB database.
6. If the connection is successful, click on the "Save" button to save your DuckDB destination connector.
7. You can now use this connector to transfer data from your source connectors to your DuckDB database. Simply select the DuckDB destination connector when setting up your data integration pipelines in Airbyte.

Step 3: Set up a connection to sync your Convex dev data to DuckDB

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

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

Use Cases to transfer your Convex dev data to DuckDB

Integrating data from Convex dev to DuckDB provides several benefits. Here are a few use cases:

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

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a Convex dev account as an Airbyte data source connector.
Configure DuckDB as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Convex dev to DuckDB 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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How to Sync Convex dev to DuckDB 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 Convex dev?

What data can you extract from Convex dev?

Convex.dev's API provides access to a wide range of data related to the cryptocurrency market. The following are the categories of data that can be accessed through the API:
‍
1. Market data: This includes real-time and historical data on cryptocurrency prices, trading volumes, market capitalization, and other market indicators.
2. Blockchain data: This includes data on transactions, blocks, and addresses on various blockchain networks.
3. Exchange data: This includes data on trading pairs, order books, and trading volumes on various cryptocurrency exchanges.
4. News data: This includes real-time news articles and updates related to the cryptocurrency market.
5. Social media data: This includes data on social media sentiment and activity related to various cryptocurrencies.
6. Technical analysis data: This includes data on technical indicators, chart patterns, and other technical analysis tools used by traders.
7. Fundamental analysis data: This includes data on the underlying fundamentals of various cryptocurrencies, such as their technology, adoption, and use cases.

Overall, Convex.dev's API provides a comprehensive set of data that can be used by traders, investors, and researchers to gain insights into the cryptocurrency market.

How do I transfer data from Convex dev?

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 Convex.dev to DuckDB 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 Convex.dev to DuckDB 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.

Back to all tutorials

Databases

How to load data from Convex dev to DuckDB

Learn how to use Airbyte to synchronize your Convex dev data into DuckDB within minutes.

Try Airbyte Cloud free

Deploy Airbyte Open Source

Step 1: Setup Convex dev

Step 2: Setup DuckDB

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Convex dev and DuckDB

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up Convex dev as a source connector (using Auth, or usually an API key)
set up DuckDB 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 Convex dev

What is DuckDB

Integrate Convex dev with DuckDB in minutes

Try for free now

Prerequisites

A Convex dev account to transfer your customer data automatically from.
A DuckDB 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.

Step 1: Set up Convex dev as a source connector

Step 2: Set up DuckDB as a destination connector

Step 3: Set up a connection to sync your Convex dev data to DuckDB

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

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

Use Cases to transfer your Convex dev data to DuckDB

Integrating data from Convex dev to DuckDB provides several benefits. Here are a few use cases:

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