Top companies trust Airbyte to centralize their Data
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.
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.
Set up a source connector to extract data from in Airbyte
Choose from one of 400 sources where you want to import data from. This can be any API tool, cloud data warehouse, database, data lake, files, among other source types. You can even build your own source connector in minutes with our no-code no-code connector builder.
Configure the connection in Airbyte
The Airbyte Open Data Movement Platform
The only open solution empowering data teams to meet growing business demands in the new AI era.
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Ship more quickly with the only solution that fits ALL your needs.
As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Ship more quickly with the only solution that fits ALL your needs.
As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Move large volumes, fast.
Change Data Capture.
Security from source to destination.
We support the CDC methods your company needs
Log-based CDC
Timestamp-based CDC
Airbyte Open Source
Airbyte Cloud
Airbyte Enterprise
Why choose Airbyte as the backbone of your data infrastructure?
Keep your data engineering costs in check
Get Airbyte hosted where you need it to be
- Airbyte Cloud: Have it hosted by us, with all the security you need (SOC2, ISO, GDPR, HIPAA Conduit).
- Airbyte Enterprise: Have it hosted within your own infrastructure, so your data and secrets never leave it.
White-glove enterprise-level support
Including for your Airbyte Open Source instance with our premium support.
Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.
Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.
Airbyte supports a growing list of sources, including API tools, cloud data warehouses, lakes, databases, and files, or even custom sources you can build.
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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.
SFTP (Secure File Transfer Protocol) is a secure way to transfer files between two computers over the internet. It uses encryption to protect the data being transferred, making it more secure than traditional FTP (File Transfer Protocol). SFTP is commonly used by businesses and organizations to transfer sensitive data such as financial information, medical records, and personal data. It requires authentication using a username and password or public key authentication, ensuring that only authorized users can access the files. SFTP is also platform-independent, meaning it can be used on any operating system, making it a versatile and reliable option for secure file transfers.
SFTP provides access to various types of data that can be used for different purposes. Some of the categories of data that SFTP's API gives access to are:
1. File data: SFTP's API allows users to access and transfer files securely over the internet. This includes uploading, downloading, and managing files.
2. User data: SFTP's API provides access to user data such as usernames, passwords, and permissions. This allows users to manage and control access to their files and folders.
3. Server data: SFTP's API gives access to server data such as server logs, server configurations, and server status. This allows users to monitor and manage their server resources.
4. Security data: SFTP's API provides access to security data such as encryption keys, certificates, and security policies. This allows users to ensure that their data is secure and protected from unauthorized access.
5. Network data: SFTP's API gives access to network data such as IP addresses, network configurations, and network traffic. This allows users to monitor and manage their network resources.
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.
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.
SFTP (Secure File Transfer Protocol) is a secure way to transfer files between two computers over the internet. It uses encryption to protect the data being transferred, making it more secure than traditional FTP (File Transfer Protocol). SFTP is commonly used by businesses and organizations to transfer sensitive data such as financial information, medical records, and personal data. It requires authentication using a username and password or public key authentication, ensuring that only authorized users can access the files. SFTP is also platform-independent, meaning it can be used on any operating system, making it a versatile and reliable option for secure file transfers.
SFTP provides access to various types of data that can be used for different purposes. Some of the categories of data that SFTP's API gives access to are:
1. File data: SFTP's API allows users to access and transfer files securely over the internet. This includes uploading, downloading, and managing files.
2. User data: SFTP's API provides access to user data such as usernames, passwords, and permissions. This allows users to manage and control access to their files and folders.
3. Server data: SFTP's API gives access to server data such as server logs, server configurations, and server status. This allows users to monitor and manage their server resources.
4. Security data: SFTP's API provides access to security data such as encryption keys, certificates, and security policies. This allows users to ensure that their data is secure and protected from unauthorized access.
5. Network data: SFTP's API gives access to network data such as IP addresses, network configurations, and network traffic. This allows users to monitor and manage their network resources.
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.
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.
SFTP (Secure File Transfer Protocol) is a secure way to transfer files between two computers over the internet. It uses encryption to protect the data being transferred, making it more secure than traditional FTP (File Transfer Protocol). SFTP is commonly used by businesses and organizations to transfer sensitive data such as financial information, medical records, and personal data. It requires authentication using a username and password or public key authentication, ensuring that only authorized users can access the files. SFTP is also platform-independent, meaning it can be used on any operating system, making it a versatile and reliable option for secure file transfers.
SFTP provides access to various types of data that can be used for different purposes. Some of the categories of data that SFTP's API gives access to are:
1. File data: SFTP's API allows users to access and transfer files securely over the internet. This includes uploading, downloading, and managing files.
2. User data: SFTP's API provides access to user data such as usernames, passwords, and permissions. This allows users to manage and control access to their files and folders.
3. Server data: SFTP's API gives access to server data such as server logs, server configurations, and server status. This allows users to monitor and manage their server resources.
4. Security data: SFTP's API provides access to security data such as encryption keys, certificates, and security policies. This allows users to ensure that their data is secure and protected from unauthorized access.
5. Network data: SFTP's API gives access to network data such as IP addresses, network configurations, and network traffic. This allows users to monitor and manage their network resources.
1. Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.
2. Click on the "Create a new connection" button and select "SFTP" as the source connector.
3. Enter a name for the connection and click "Next".
4. In the "Connection Configuration" section, enter the hostname or IP address of the SFTP server, as well as the port number (usually 22).
5. Enter the username and password for the SFTP server in the "Authentication" section.
6. If your SFTP server requires a private key for authentication, select the "Private Key" option and enter the path to the key file.
7. In the "Advanced" section, you can specify additional options such as the path to the remote directory and the file pattern to use for selecting files.
8. Click "Test" to verify that the connection is working correctly.
9. If the test is successful, click "Create" to save the connection and start syncing data from the SFTP server.
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.
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