Building your pipeline or Using Airbyte
Airbyte is the only open 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
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
"The intake layer of Datadog’s self-serve analytics platform is largely built on Airbyte.Airbyte’s ease of use and extensibility allowed any team in the company to push their data into the platform - without assistance from the data team!"
“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.”
“We chose Airbyte for its ease of use, its pricing scalability and its absence of vendor lock-in. Having a lean team makes them our top criteria. The value of being able to scale and execute at a high level by maximizing resources is immense”
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.
Braze is a customer engagement platform that helps businesses build meaningful relationships with their customers. It offers a suite of tools for creating personalized and relevant messaging across multiple channels, including email, push notifications, in-app messaging, and more. With Braze, businesses can track customer behavior and preferences, segment their audience, and deliver targeted campaigns that drive engagement and revenue. The platform also includes advanced analytics and reporting capabilities, allowing businesses to measure the impact of their campaigns and optimize their strategies over time. Overall, Braze helps businesses create more effective and engaging customer experiences that drive loyalty and growth.
Braze's API provides access to a wide range of data related to customer engagement and marketing campaigns. The following are the categories of data that can be accessed through Braze's API:
1. User data: This includes information about individual users such as their name, email address, phone number, and location.
2. Campaign data: This includes data related to marketing campaigns such as email campaigns, push notifications, and in-app messages. It includes information about the campaign's performance, such as open rates, click-through rates, and conversion rates.
3. Event data: This includes data related to user actions such as app installs, purchases, and other interactions with the app or website.
4. Segmentation data: This includes data related to user segments, such as demographics, behavior, and interests.
5. Messaging data: This includes data related to messaging channels such as email, push notifications, and in-app messages. It includes information about message content, delivery, and engagement.
6. Analytics data: This includes data related to user behavior and engagement, such as session length, retention rates, and revenue generated.
Overall, Braze's API provides access to a wealth of data that can be used to optimize marketing campaigns and improve customer engagement.
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.
Braze is a customer engagement platform that helps businesses build meaningful relationships with their customers. It offers a suite of tools for creating personalized and relevant messaging across multiple channels, including email, push notifications, in-app messaging, and more. With Braze, businesses can track customer behavior and preferences, segment their audience, and deliver targeted campaigns that drive engagement and revenue. The platform also includes advanced analytics and reporting capabilities, allowing businesses to measure the impact of their campaigns and optimize their strategies over time. Overall, Braze helps businesses create more effective and engaging customer experiences that drive loyalty and growth.
For huge analytical tables, Apache Iceberg is a high-performance format. Using Apache Iceberg, engines such as Spark, Trino, Flink, Presto, Hive and Impala can safely work with the same tables, at the same time, providing the reliability and simplicity of SQL tables to big data. With Apache Iceberg, you can merge new data, update existing rows, and delete specific rows. Data files can be eagerly rewritten or deleted deltas can be used to make updates faster.
1. First, navigate to the Braze source connector page on Airbyte.com.
2. Click on the "Create a new Braze source" button.
3. Enter a name for your Braze source connector.
4. Enter your Braze API key and secret key in the appropriate fields.
5. Select the Braze API endpoint you want to use (REST or Export API).
6. Choose the data you want to replicate from Braze by selecting the appropriate tables and fields.
7. Test the connection to ensure that the credentials are correct and the connection is successful.
8. Save the Braze source connector configuration.
9. Run the Braze source connector to start replicating data from Braze to your destination.
1. Open the Airbyte platform and navigate to the "Destinations" tab on the left-hand side of the screen.
2. Click on the "Apache Iceberg" destination connector and select "Create new connection."
3. Enter a name for your connection and provide the necessary credentials for your Apache Iceberg database, including the host, port, database name, username, and password.
4. Test the connection to ensure that it is successful. 5. Select the tables or data sources that you want to replicate to your Apache Iceberg database.
6. Configure any additional settings or options for your connection, such as the frequency of data replication or any transformations that you want to apply to your data.
7. Save your connection and start the replication process.
8. Monitor the progress of your data replication and troubleshoot any issues that may arise.
9. Once the replication process is complete, verify that your data has been successfully replicated to your Apache Iceberg database.
10. Use your Apache Iceberg database to analyze and query your data as needed.
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:
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
Ready to get started?
Frequently Asked Questions
Braze's API provides access to a wide range of data related to customer engagement and marketing campaigns. The following are the categories of data that can be accessed through Braze's API:
1. User data: This includes information about individual users such as their name, email address, phone number, and location.
2. Campaign data: This includes data related to marketing campaigns such as email campaigns, push notifications, and in-app messages. It includes information about the campaign's performance, such as open rates, click-through rates, and conversion rates.
3. Event data: This includes data related to user actions such as app installs, purchases, and other interactions with the app or website.
4. Segmentation data: This includes data related to user segments, such as demographics, behavior, and interests.
5. Messaging data: This includes data related to messaging channels such as email, push notifications, and in-app messages. It includes information about message content, delivery, and engagement.
6. Analytics data: This includes data related to user behavior and engagement, such as session length, retention rates, and revenue generated.
Overall, Braze's API provides access to a wealth of data that can be used to optimize marketing campaigns and improve customer engagement.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey: