How to load data from TMDb to Convex

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

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Set up a TMDb connector in Airbyte

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

Set up Convex for your extracted TMDb data

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

Configure the TMDb to Convex 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

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 TMDb as a source connector (using Auth, or usually an API key)
  2. set up Convex as a destination connector
  3. 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 TMDb

TMDb is a community built movie and TV database. The Movie Database (TMDb) is a well known, popular, user editable database for movies and TV shows. TMDb.org, which is a crowd-sourced movie information database used by many film-related consoles, sites and apps, like XBMC, Myth TV and Plex. The Movie Database (TMDb) is a database of TV shows and movies which permits users to edit data. Since 2008, the users have been editing and adding the data through TMDb.

What is Convex

Convex is a platform that provides a suite of tools for building and deploying machine learning models. It offers a user-friendly interface for data scientists and developers to create and train models, as well as a scalable infrastructure for deploying them in production. Convex also includes features such as automated model tuning, version control, and collaboration tools to streamline the machine learning workflow. The platform is designed to be flexible and customizable, allowing users to integrate their own libraries and frameworks. Overall, Convex aims to simplify the process of building and deploying machine learning models, making it accessible to a wider range of users.

Integrate TMDb with Convex in minutes

Try for free now

Prerequisites

  1. A TMDb account to transfer your customer data automatically from.
  2. A Convex account.
  3. 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 TMDb and Convex, for seamless data migration.

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

Step 1: Set up TMDb as a source connector

1. First, navigate to the TMDb website and create an account if you haven't already done so.
2. Once you have an account, log in and navigate to your account settings.
3. In your account settings, click on the "API" tab.
4. On the API page, click the "Generate new API key" button to create a new API key.
5. Give your API key a name and select the appropriate permissions for your use case.
6. Copy the API key that is generated.
7. Navigate to Airbyte and click on "Sources" in the left-hand menu.
8. Click the "New Source" button and select "TMDb" from the list of available connectors.
9. Enter a name for your TMDb source and paste the API key you copied earlier into the "API Key" field.
10. Click the "Test" button to ensure that your credentials are valid and that Airbyte can connect to your TMDb account.
11. If the test is successful, click the "Create" button to save your TMDb source and begin syncing data.

Step 2: Set up Convex 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. From there, click on the "Add Destination" button in the top right corner of the screen.
4. In the search bar, type "Convex" and select the Convex destination connector from the list of options.
5. Next, you will need to enter your Convex API key. This can be found in your Convex account settings.
6. Once you have entered your API key, click on the "Test" button to ensure that the connection is working properly.
7. If the test is successful, click on the "Save" button to save your settings.
8. You can now use the Convex destination connector to transfer data from Airbyte to your Convex account.

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

Once you've successfully connected TMDb as a data source and Convex as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

  1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
  2. Choose your source: Select TMDb from the dropdown list of your configured sources.
  3. Select your destination: Choose Convex from the dropdown list of your configured destinations.
  4. 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.
  5. Select the data to sync: Choose the specific TMDb objects you want to import data from towards Convex. You can sync all data or select specific tables and fields.
  6. 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.
  7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
  8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from TMDb to Convex according to your settings.

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

Use Cases to transfer your TMDb data to Convex

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

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

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a TMDb account as an Airbyte data source connector.
  2. Configure Convex as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from TMDb to Convex 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!

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

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Sync with Airbyte

How to Sync TMDb to Convex Manually

FAQs

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.

TMDb is a community built movie and TV database. The Movie Database (TMDb) is a well known, popular, user editable database for movies and TV shows. TMDb.org, which is a crowd-sourced movie information database used by many film-related consoles, sites and apps, like XBMC, Myth TV and Plex. The Movie Database (TMDb) is a database of TV shows and movies which permits users to edit data. Since 2008, the users have been editing and adding the data through TMDb.

The TMDb (The Movie Database) API provides access to a wide range of data related to movies and TV shows. The following are the categories of data that can be accessed through the TMDb API:  

- Movie data: This includes information about movies such as title, release date, runtime, budget, revenue, genres, production companies, and more.
- TV show data: This includes information about TV shows such as title, air date, episode count, season count, networks, genres, and more.
- People data: This includes information about people involved in movies and TV shows such as actors, directors, writers, and producers.
- Keyword data: This includes information about keywords associated with movies and TV shows such as plot keywords, genres, and more.
- Collection data: This includes information about collections of movies such as franchises, trilogies, and more.
- Review data: This includes information about reviews of movies and TV shows such as user ratings and reviews.
- Image data: This includes images related to movies and TV shows such as posters, backdrops, and stills.

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 TMDb to Convex 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 TMDb to Convex and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud. 

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.

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
Engineering Analytics
Others

How to load data from TMDb to Convex

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

TL;DR
What is TMDb
What is Convex
Prerequisites
Step 1: Setup TMDb
Step 2: Setup Convex
Step 3: Setup a connectionUse CasesWrapping Up
Example H2
Example H3

Sync data between TMDb and Convex

Try Airbyte free

TL;DR

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 TMDb as a source connector (using Auth, or usually an API key)
  2. set up Convex as a destination connector
  3. 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 TMDb

TMDb is a community built movie and TV database. The Movie Database (TMDb) is a well known, popular, user editable database for movies and TV shows. TMDb.org, which is a crowd-sourced movie information database used by many film-related consoles, sites and apps, like XBMC, Myth TV and Plex. The Movie Database (TMDb) is a database of TV shows and movies which permits users to edit data. Since 2008, the users have been editing and adding the data through TMDb.

What is Convex

Convex is a platform that provides a suite of tools for building and deploying machine learning models. It offers a user-friendly interface for data scientists and developers to create and train models, as well as a scalable infrastructure for deploying them in production. Convex also includes features such as automated model tuning, version control, and collaboration tools to streamline the machine learning workflow. The platform is designed to be flexible and customizable, allowing users to integrate their own libraries and frameworks. Overall, Convex aims to simplify the process of building and deploying machine learning models, making it accessible to a wider range of users.

Integrate TMDb with Convex in minutes

Try for free now

Prerequisites

  1. A TMDb account to transfer your customer data automatically from.
  2. A Convex account.
  3. 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 TMDb and Convex, for seamless data migration.

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

Step 1: Set up TMDb as a source connector

1. First, navigate to the TMDb website and create an account if you haven't already done so.
2. Once you have an account, log in and navigate to your account settings.
3. In your account settings, click on the "API" tab.
4. On the API page, click the "Generate new API key" button to create a new API key.
5. Give your API key a name and select the appropriate permissions for your use case.
6. Copy the API key that is generated.
7. Navigate to Airbyte and click on "Sources" in the left-hand menu.
8. Click the "New Source" button and select "TMDb" from the list of available connectors.
9. Enter a name for your TMDb source and paste the API key you copied earlier into the "API Key" field.
10. Click the "Test" button to ensure that your credentials are valid and that Airbyte can connect to your TMDb account.
11. If the test is successful, click the "Create" button to save your TMDb source and begin syncing data.

Step 2: Set up Convex 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. From there, click on the "Add Destination" button in the top right corner of the screen.
4. In the search bar, type "Convex" and select the Convex destination connector from the list of options.
5. Next, you will need to enter your Convex API key. This can be found in your Convex account settings.
6. Once you have entered your API key, click on the "Test" button to ensure that the connection is working properly.
7. If the test is successful, click on the "Save" button to save your settings.
8. You can now use the Convex destination connector to transfer data from Airbyte to your Convex account.

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

Once you've successfully connected TMDb as a data source and Convex as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

  1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
  2. Choose your source: Select TMDb from the dropdown list of your configured sources.
  3. Select your destination: Choose Convex from the dropdown list of your configured destinations.
  4. 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.
  5. Select the data to sync: Choose the specific TMDb objects you want to import data from towards Convex. You can sync all data or select specific tables and fields.
  6. 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.
  7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
  8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from TMDb to Convex according to your settings.

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

Use Cases to transfer your TMDb data to Convex

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

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

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a TMDb account as an Airbyte data source connector.
  2. Configure Convex as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from TMDb to Convex 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!

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

Connectors Used

TMDb
Convex

Related Syncs with TMDb

Tags

Integration Platforms

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

Connectors Used

TMDb
Convex

Related Syncs with TMDb

TMDb to Convex
TMDb to RabbitMQ
TMDb to Typesense
TMDb to Weaviate

Tags

Integration Platforms

Ready to get started?

Try Airbyte Cloud freeTalk to our team

Frequently Asked Questions

What data can you extract from TMDb?

The TMDb (The Movie Database) API provides access to a wide range of data related to movies and TV shows. The following are the categories of data that can be accessed through the TMDb API:  

- Movie data: This includes information about movies such as title, release date, runtime, budget, revenue, genres, production companies, and more.
- TV show data: This includes information about TV shows such as title, air date, episode count, season count, networks, genres, and more.
- People data: This includes information about people involved in movies and TV shows such as actors, directors, writers, and producers.
- Keyword data: This includes information about keywords associated with movies and TV shows such as plot keywords, genres, and more.
- Collection data: This includes information about collections of movies such as franchises, trilogies, and more.
- Review data: This includes information about reviews of movies and TV shows such as user ratings and reviews.
- Image data: This includes images related to movies and TV shows such as posters, backdrops, and stills.

What data can you transfer to Convex?

You can transfer a wide variety of data to Convex. This usually includes structured, semi-structured, and unstructured data like transaction records, log files, JSON data, CSV files, and more, allowing robust, scalable data integration and analysis.

What are top ETL tools to transfer data from TMDb to Convex?

The most prominent ETL tools to transfer data from TMDb to Convex include:

  • Airbyte
  • Fivetran
  • Stitch
  • Matillion
  • Talend Data Integration

These tools help in extracting data from TMDb and various sources (APIs, databases, and more), transforming it efficiently, and loading it into Convex and other databases, data warehouses and data lakes, enhancing data management capabilities.

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

Connectors Used

TMDb
Convex

Related Syncs with TMDb

TMDb to Convex
TMDb to RabbitMQ
TMDb to Typesense
TMDb to Weaviate

Tags

Integration Platforms

Connectors Used

TMDb
Convex

Related Syncs with TMDb

TMDb to Convex
TMDb to RabbitMQ
TMDb to Typesense
TMDb to Weaviate

Tags

Integration Platforms