How to load data from S3 to MS SQL Server

Learn how to use Airbyte to synchronize your S3 data into MS SQL Server within minutes.

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Set up a S3 connector in Airbyte

Connect to S3 or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up MS SQL Server for your extracted S3 data

Connect to S3 or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Configure the S3 to MS SQL Server 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 S3 as a source connector (using Auth, or usually an API key)
  2. set up MS SQL Server 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 S3

Amazon S3 (Simple Storage Service) is a cloud-based object storage service that provides developers and IT teams with secure, durable, and scalable storage for their data. It allows users to store and retrieve any amount of data from anywhere on the web, making it easy to build and scale applications, backup and archive data, and analyze data. S3 is designed to provide high availability and durability, with data automatically replicated across multiple availability zones within a region. It also offers a range of features such as versioning, lifecycle policies, and access control to help users manage their data effectively.

What is MS SQL Server

Microsoft SQL Server is a relational database management (RDBMS) built by Microsoft. As a database server, its primary function is to store and retrieve data upon the request of other software applications, either from the same computer or a different computer across a network—including the internet. To serve the needs of different audiences and workload sizes, Microsoft offers multiple editions (at least 12) of its Microsoft SQL Server.

Integrate S3 with MS SQL Server in minutes

Try for free now

Prerequisites

  1. A S3 account to transfer your customer data automatically from.
  2. A MS SQL Server 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 S3 and MS SQL Server, for seamless data migration.

When using Airbyte to move data from S3 to MS SQL Server, it extracts data from S3 using the source connector, converts it into a format MS SQL Server can ingest using the provided schema, and then loads it into MS SQL Server via the destination connector. This allows businesses to leverage their S3 data for advanced analytics and insights within MS SQL Server, simplifying the ETL process and saving significant time and resources.

Step 1: Set up S3 as a source connector

1. Open the Airbyte dashboard and click on "Sources" from the left-hand menu.
2. Click on the "Create Source" button and select "S3" from the list of available connectors.
3. Enter a name for your S3 source and click on "Next".
4. Enter your AWS access key ID and secret access key in the respective fields. You can find these credentials in your AWS account under "Security Credentials".
5. Select the AWS region where your S3 bucket is located from the dropdown menu.
6. Enter the name of your S3 bucket in the "Bucket Name" field.
7. If your S3 bucket is not in the root directory, enter the path to the directory in the "Path Prefix" field.
8. If you want to include only certain files in your data sync, you can enter a file pattern in the "File Pattern" field. For example, "*.csv" will only include CSV files.
9. Click on "Test" to verify your credentials and connection to the S3 bucket.
10. If the test is successful, click on "Create Source" to save your S3 source connector.Once your S3 source connector is set up, you can use it to create a new Airbyte pipeline and sync data from your S3 bucket to your destination of choice.

Step 2: Set up MS SQL Server as a destination connector

1. Open the Airbyte platform and navigate to the "Destinations" tab on the left-hand side of the screen.
2. Scroll down until you find the "MSSQL - SQL Server" connector and click on it.
3. Click on the "Create new destination" button.
4. Fill in the required information, including the destination name, host, port, database name, username, and password.
5. Click on the "Test connection" button to ensure that the connection is successful.
6. Once the connection is successful, click on the "Save" button to save the destination.
7. Navigate to the "Sources" tab on the left-hand side of the screen and select the source that you want to connect to the MSSQL - SQL Server destination.
8. Click on the "Create new connection" button.
9. Select the MSSQL - SQL Server destination that you just created from the drop-down menu.
10. Fill in the required information for the source, including the source name, host, port, database name, username, and password.
11. Click on the "Test connection" button to ensure that the connection is successful.
12. Once the connection is successful, click on the "Save" button to save the connection.13. You can now start syncing data from your source to your MSSQL - SQL Server destination.

Step 3: Set up a connection to sync your S3 data to MS SQL Server

Once you've successfully connected S3 as a data source and MS SQL Server 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 S3 from the dropdown list of your configured sources.
  3. Select your destination: Choose MS SQL Server 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 S3 objects you want to import data from towards MS SQL Server. 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 S3 to MS SQL Server according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your MS SQL Server data warehouse is always up-to-date with your S3 data.

Use Cases to transfer your S3 data to MS SQL Server

Integrating data from S3 to MS SQL Server provides several benefits. Here are a few use cases:

  1. Advanced Analytics: MS SQL Server’s powerful data processing capabilities enable you to perform complex queries and data analysis on your S3 data, extracting insights that wouldn't be possible within S3 alone.
  2. Data Consolidation: If you're using multiple other sources along with S3, syncing to MS SQL Server 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: S3 has limits on historical data. Syncing data to MS SQL Server allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: MS SQL Server provides robust data security features. Syncing S3 data to MS SQL Server ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: MS SQL Server can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding S3 data.
  6. Data Science and Machine Learning: By having S3 data in MS SQL Server, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While S3 provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to MS SQL Server, providing more advanced business intelligence options. If you have a S3 table that needs to be converted to a MS SQL Server table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a S3 account as an Airbyte data source connector.
  2. Configure MS SQL Server as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from S3 to MS SQL Server 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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Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
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Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
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How to Sync S3 to MS SQL Server Manually

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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.

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Warehouses and Lakes

How to load data from S3 to MS SQL Server

Learn how to use Airbyte to synchronize your S3 data into MS SQL Server within minutes.

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 S3 as a source connector (using Auth, or usually an API key)
  2. set up MS SQL Server 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 S3

Amazon S3 (Simple Storage Service) is a cloud-based object storage service that provides developers and IT teams with secure, durable, and scalable storage for their data. It allows users to store and retrieve any amount of data from anywhere on the web, making it easy to build and scale applications, backup and archive data, and analyze data. S3 is designed to provide high availability and durability, with data automatically replicated across multiple availability zones within a region. It also offers a range of features such as versioning, lifecycle policies, and access control to help users manage their data effectively.

What is MS SQL Server

Microsoft SQL Server is a relational database management (RDBMS) built by Microsoft. As a database server, its primary function is to store and retrieve data upon the request of other software applications, either from the same computer or a different computer across a network—including the internet. To serve the needs of different audiences and workload sizes, Microsoft offers multiple editions (at least 12) of its Microsoft SQL Server.

Integrate S3 with MS SQL Server in minutes

Try for free now

Prerequisites

  1. A S3 account to transfer your customer data automatically from.
  2. A MS SQL Server 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 S3 and MS SQL Server, for seamless data migration.

When using Airbyte to move data from S3 to MS SQL Server, it extracts data from S3 using the source connector, converts it into a format MS SQL Server can ingest using the provided schema, and then loads it into MS SQL Server via the destination connector. This allows businesses to leverage their S3 data for advanced analytics and insights within MS SQL Server, simplifying the ETL process and saving significant time and resources.

Step 1: Set up S3 as a source connector

1. Open the Airbyte dashboard and click on "Sources" from the left-hand menu.
2. Click on the "Create Source" button and select "S3" from the list of available connectors.
3. Enter a name for your S3 source and click on "Next".
4. Enter your AWS access key ID and secret access key in the respective fields. You can find these credentials in your AWS account under "Security Credentials".
5. Select the AWS region where your S3 bucket is located from the dropdown menu.
6. Enter the name of your S3 bucket in the "Bucket Name" field.
7. If your S3 bucket is not in the root directory, enter the path to the directory in the "Path Prefix" field.
8. If you want to include only certain files in your data sync, you can enter a file pattern in the "File Pattern" field. For example, "*.csv" will only include CSV files.
9. Click on "Test" to verify your credentials and connection to the S3 bucket.
10. If the test is successful, click on "Create Source" to save your S3 source connector.Once your S3 source connector is set up, you can use it to create a new Airbyte pipeline and sync data from your S3 bucket to your destination of choice.

Step 2: Set up MS SQL Server as a destination connector

1. Open the Airbyte platform and navigate to the "Destinations" tab on the left-hand side of the screen.
2. Scroll down until you find the "MSSQL - SQL Server" connector and click on it.
3. Click on the "Create new destination" button.
4. Fill in the required information, including the destination name, host, port, database name, username, and password.
5. Click on the "Test connection" button to ensure that the connection is successful.
6. Once the connection is successful, click on the "Save" button to save the destination.
7. Navigate to the "Sources" tab on the left-hand side of the screen and select the source that you want to connect to the MSSQL - SQL Server destination.
8. Click on the "Create new connection" button.
9. Select the MSSQL - SQL Server destination that you just created from the drop-down menu.
10. Fill in the required information for the source, including the source name, host, port, database name, username, and password.
11. Click on the "Test connection" button to ensure that the connection is successful.
12. Once the connection is successful, click on the "Save" button to save the connection.13. You can now start syncing data from your source to your MSSQL - SQL Server destination.

Step 3: Set up a connection to sync your S3 data to MS SQL Server

Once you've successfully connected S3 as a data source and MS SQL Server 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 S3 from the dropdown list of your configured sources.
  3. Select your destination: Choose MS SQL Server 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 S3 objects you want to import data from towards MS SQL Server. 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 S3 to MS SQL Server according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your MS SQL Server data warehouse is always up-to-date with your S3 data.

Use Cases to transfer your S3 data to MS SQL Server

Integrating data from S3 to MS SQL Server provides several benefits. Here are a few use cases:

  1. Advanced Analytics: MS SQL Server’s powerful data processing capabilities enable you to perform complex queries and data analysis on your S3 data, extracting insights that wouldn't be possible within S3 alone.
  2. Data Consolidation: If you're using multiple other sources along with S3, syncing to MS SQL Server 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: S3 has limits on historical data. Syncing data to MS SQL Server allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: MS SQL Server provides robust data security features. Syncing S3 data to MS SQL Server ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: MS SQL Server can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding S3 data.
  6. Data Science and Machine Learning: By having S3 data in MS SQL Server, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While S3 provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to MS SQL Server, providing more advanced business intelligence options. If you have a S3 table that needs to be converted to a MS SQL Server table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a S3 account as an Airbyte data source connector.
  2. Configure MS SQL Server as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from S3 to MS SQL Server 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

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

Frequently Asked Questions

What data can you extract from S3?

Amazon S3's API provides access to a wide range of data types, including:

1. Object data: This includes the actual files stored in S3 buckets, such as images, videos, documents, and other types of files.
2. Metadata: S3 stores metadata about each object, including information such as the object's size, creation date, and last modified date.
3. Access control data: S3 provides access control mechanisms to restrict access to objects in a bucket. The API provides access to information about access control policies and permissions.
4. Bucket data: S3 buckets are containers for objects. The API provides access to information about buckets, such as their names, creation dates, and region.
5. Logging data: S3 can log access requests to objects in a bucket. The API provides access to these logs, which can be used for auditing and compliance purposes.
6. Inventory data: S3 can generate inventory reports that provide information about the objects stored in a bucket. The API provides access to these reports.
7. Metrics data: S3 can generate metrics about the usage of a bucket, such as the number of requests and the amount of data transferred. The API provides access to these metrics.

What data can you transfer to MS SQL Server?

You can transfer a wide variety of data to MS SQL Server. 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 S3 to MS SQL Server?

The most prominent ETL tools to transfer data from S3 to MS SQL Server include:

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

These tools help in extracting data from S3 and various sources (APIs, databases, and more), transforming it efficiently, and loading it into MS SQL Server 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