How to load data from Azure Table Storage to Convex

Learn how to use Airbyte to synchronize your Azure Table Storage data into Convex within minutes.

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Set up a Azure Table Storage connector in Airbyte

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

Set up Convex for your extracted Azure Table Storage data

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

Configure the Azure Table Storage 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

set up Azure Table Storage as a source connector (using Auth, or usually an API key)
set up Convex 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 Azure Table Storage

Azure Table storage, which is a service that stores non-relational structured data in the cloud and it is well known as structured NoSQL data. Azure Table storage is a service that stores structured NoSQL data in the cloud, providing a key/attribute store with a schema less design. Azure Table storage is a very popular service used to store structured NoSQL data in the cloud, providing a Key/attribute store. One can use it to store large amounts of structured, non-relational data.

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 Azure Table Storage with Convex in minutes

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Prerequisites

A Azure Table Storage account to transfer your customer data automatically from.
A Convex 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 Azure Table Storage and Convex, for seamless data migration.

When using Airbyte to move data from Azure Table Storage to Convex, it extracts data from Azure Table Storage 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 Azure Table Storage data for advanced analytics and insights within Convex, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Azure Table Storage as a source connector

1. First, you need to create an Azure Table Storage account and obtain the account name and account key. You can find these details in the Azure portal under the "Access keys" section of your storage account.
2. In Airbyte, navigate to the "Sources" tab and click on "Add Source". Select "Azure Table Storage" from the list of available sources.
3. In the "Configure Azure Table Storage" page, enter the account name and account key that you obtained in step 1.
4. Next, enter the name of the table that you want to connect to. You can find the name of the table in the Azure portal under the "Tables" section of your storage account.
5. If you want to filter the data that you retrieve from the table, you can enter a filter expression in the "Filter" field. This expression should be in the OData syntax.
6. Finally, click on "Test Connection" to ensure that Airbyte can connect to your Azure Table Storage account. If the connection is successful, click on "Create Source" to save your configuration.
7. You can now use this source to create a new Airbyte pipeline and start replicating data from your Azure Table Storage account.

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 Azure Table Storage data to Convex

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

Use Cases to transfer your Azure Table Storage data to Convex

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

Advanced Analytics: Convex’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Azure Table Storage data, extracting insights that wouldn't be possible within Azure Table Storage alone.
Data Consolidation: If you're using multiple other sources along with Azure Table Storage, 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.
Historical Data Analysis: Azure Table Storage has limits on historical data. Syncing data to Convex allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Convex provides robust data security features. Syncing Azure Table Storage data to Convex ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Convex can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Azure Table Storage data.
Data Science and Machine Learning: By having Azure Table Storage data in Convex, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Azure Table Storage 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 Azure Table Storage 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:

Configure a Azure Table Storage account as an Airbyte data source connector.
Configure Convex as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Azure Table Storage 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!

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Sync with Airbyte

Step 1: Set up Azure Table Storage as a source connector

Step 2: Set up Convex as a destination connector

Step 3: Set up a connection to sync your Azure Table Storage data to Convex

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

How to Sync Azure Table Storage to Convex 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 Azure Table Storage?

What data can you extract from Azure Table Storage?

Azure Table Storage's API gives access to structured data in the form of tables. The tables are composed of rows and columns, and each row represents an entity. The API provides access to the following types of data:

1. Partition Key: A partition key is a property that is used to partition the data in a table. It is used to group related entities together.
2. Row Key: A row key is a unique identifier for an entity within a partition. It is used to retrieve a specific entity from the table.
3. Properties: Properties are the columns in a table. They represent the attributes of an entity and can be of different data types such as string, integer, boolean, etc.
4. Timestamp: The timestamp is a system-generated property that represents the time when an entity was last modified.
5. ETag: The ETag is a system-generated property that represents the version of an entity. It is used to implement optimistic concurrency control.
6. Query results: The API allows querying of the data in a table based on specific criteria. The query results can be filtered, sorted, and projected to retrieve only the required data.

Overall, Azure Table Storage's API provides access to structured data that can be used for various purposes such as storing configuration data, logging, and session state management.

‍

How do I transfer data from Azure Table Storage?

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 Azure Table Storage 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 Azure Table Storage 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.

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

Engineering Analytics

Warehouses and Lakes

How to load data from Azure Table Storage to Convex

Learn how to use Airbyte to synchronize your Azure Table Storage data into Convex within minutes.

Try Airbyte Cloud free

Deploy Airbyte Open Source

TL;DR

What is Azure Table Storage

What is Convex

Prerequisites

Step 1: Setup Azure Table Storage

Step 2: Setup Convex

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Azure Table Storage and Convex

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up Azure Table Storage as a source connector (using Auth, or usually an API key)
set up Convex 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 Azure Table Storage

What is Convex

Integrate Azure Table Storage with Convex in minutes

Try for free now

Prerequisites

A Azure Table Storage account to transfer your customer data automatically from.
A Convex 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 Azure Table Storage as a source connector

Step 2: Set up Convex as a destination connector

Step 3: Set up a connection to sync your Azure Table Storage data to Convex

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

Use Cases to transfer your Azure Table Storage data to Convex

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

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