Trusted by data-driven companies
Building your pipeline or Using Airbyte
Airbyte is the only open source solution empowering data teams to meet all their growing custom business demands in the new AI era.
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
- Reliable and accurate
- Extensible and scalable for all your needs
- Deployed and governed your way
Start syncing with Airbyte in 3 easy steps within 10 minutes
Take a virtual tour
Demo video of Airbyte Cloud
Demo video of AI Connector Builder
Setup Complexities simplified!
Simple & Easy to use Interface
Airbyte is built to get out of your way. Our clean, modern interface walks you through setup, so you can go from zero to sync in minutes—without deep technical expertise.
Guided Tour: Assisting you in building connections
Whether you’re setting up your first connection or managing complex syncs, Airbyte’s UI and documentation help you move with confidence. No guesswork. Just clarity.
Airbyte AI Assistant that will act as your sidekick in building your data pipelines in Minutes
Airbyte’s built-in assistant helps you choose sources, set destinations, and configure syncs quickly. It’s like having a data engineer on call—without the overhead.
What sets Airbyte Apart
Modern GenAI Workflows
Move Large Volumes, Fast
An Extensible Open-Source Standard
Full Control & Security
Fully Featured & Integrated
Enterprise Support with SLAs
What our users say
Andre Exner
"For TUI Musement, Airbyte cut development time in half and enabled dynamic customer experiences."
Chase Zieman
“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”
Rupak Patel
"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."
CommCare allows you to export data in various formats, such as Excel or CSV. Log into your CommCare account, navigate to the data export section, and select the forms or cases you wish to export. Choose CSV as the export format, as it is straightforward to work with for database imports.
Once you have the CSV file, open it in a spreadsheet application like Microsoft Excel or Google Sheets. Clean the data by ensuring that there are no formatting issues, remove any unnecessary columns, and make sure the data types align with those in your MS SQL database schema. Save the cleaned file.
Access your MS SQL Server and create a database or choose an existing one where you want to import the data. Create tables with the appropriate schema to match the structure of the data in your CSV file. Ensure that data types and column names are consistent with the data you plan to import.
Open SQL Server Management Studio and connect to your SQL Server instance. Use the Import and Export Wizard to facilitate the import process. Right-click on the database where you want to import data, navigate to 'Tasks', and select 'Import Data'.
In the Import and Export Wizard, select 'Flat File Source' as the data source, and browse to your CSV file. Configure the settings according to your data, such as text qualifiers and delimiters. Ensure that the destination is set to your MS SQL database and map the CSV columns to the appropriate table columns.
Review the data mapping to ensure everything is correctly aligned, and then proceed to execute the import process. The wizard will import the data from the CSV file into your MS SQL database table. Monitor the process for any potential errors and make adjustments if necessary.
After the import is complete, run SQL queries to verify that the data has been accurately imported into your tables. Check for any discrepancies or data integrity issues. If everything looks good, finalize the process by deleting any intermediary files and documenting the import procedure for future reference.
By following these steps, you can effectively transfer data from CommCare to an MS SQL database without relying on third-party connectors or integrations.
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.
Commcare is a mobile data collection and management platform designed for frontline workers in low-resource settings. It allows users to create custom mobile applications that can be used to collect data, track progress, and manage workflows. The platform is designed to be user-friendly and accessible, even for users with limited technical skills. Commcare is used by organizations in a variety of sectors, including healthcare, agriculture, and education, to improve data collection and management, increase efficiency, and improve outcomes. The platform is highly customizable, allowing users to tailor their applications to their specific needs and workflows.
Commcare's API provides access to a wide range of data related to mobile data collection and management. The following are the categories of data that can be accessed through Commcare's API:
1. Form Data: This includes data collected through mobile forms, such as survey responses, patient information, and other data points.
2. Case Data: This includes data related to cases created in Commcare, such as patient cases, project cases, and other case types.
3. User Data: This includes data related to users of the Commcare platform, such as user profiles, roles, and permissions.
4. Location Data: This includes data related to the location of mobile devices used for data collection, such as GPS coordinates and other location-based data.
5. Analytics Data: This includes data related to the performance of mobile data collection and management, such as usage statistics, form completion rates, and other metrics.
6. Media Data: This includes data related to media files uploaded through Commcare, such as images, videos, and audio recordings.
Overall, Commcare's API provides access to a wide range of data that can be used to improve mobile data collection and management processes.
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 should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
