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."
To access SMS data from Mailjet, ensure your account is configured for API access. Log into your Mailjet account and navigate to 'Account Settings' to create or retrieve your API key and secret. This will allow you to programmatically access your SMS data.
Use the Mailjet SMS API to extract the data you need. You can write a script in a language like Python, Node.js, or Java that sends HTTP GET requests to the Mailjet SMS API endpoint. This script should handle authentication using your API key and secret and retrieve the SMS data in a structured format, such as JSON.
Once you've retrieved the data, process and format it as needed. This might involve converting the JSON data into CSV or another format suitable for your analysis or storage requirements. Use libraries like `pandas` in Python for data manipulation and conversion.
Log into your AWS Management Console and navigate to S3. Create a new bucket or choose an existing one where you will store your SMS data. Ensure you configure the bucket permissions to allow access to the data you will upload.
Install the AWS CLI on your local machine and configure it with the necessary credentials. Run `aws configure` and input your AWS Access Key ID, Secret Access Key, region, and output format. This setup will allow your local environment to interact with AWS services securely.
In your script, use the AWS SDK for your chosen programming language (such as Boto3 for Python) to upload the formatted SMS data to your S3 bucket. This involves writing a function that utilizes the SDK's S3 upload method, specifying the bucket name and the file path of the data to be uploaded.
To ensure regular data updates, automate the above script using a cron job (on Unix-based systems) or Task Scheduler (on Windows). Set the job to run at your desired frequency, ensuring that it regularly extracts, processes, and uploads SMS data from Mailjet to your S3 bucket without manual intervention.
By following these steps, you can efficiently move data from Mailjet SMS to Amazon S3 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.
Mailjet is one of the affordable software for email marketing campaigns SMS campaigns, newsletter creation, email template building etc. Mailjet permits you to send transactional SMS messages using our Send SMS API. The Mailjet Transactional SMS API offers a straight-forward way to add SMS functionalities to third-party applications. Mailjet's SMS API allows you to send text messages to users around the globe through a simple RESTful API.
Mailjet SMS's API provides access to various types of data related to SMS messaging. The categories of data that can be accessed through the API are as follows:
1. Account data: This includes information about the user's Mailjet SMS account, such as account ID, API key, and account balance.
2. Message data: This includes details about the SMS messages sent and received through the Mailjet SMS platform, such as message ID, sender ID, recipient number, message content, and delivery status.
3. Contact data: This includes information about the contacts or recipients of SMS messages, such as contact ID, phone number, and contact attributes.
4. Campaign data: This includes data related to SMS campaigns, such as campaign ID, campaign name, and campaign statistics.
5. Analytics data: This includes data related to SMS message performance, such as delivery rates, open rates, click-through rates, and conversion rates.
6. Integration data: This includes data related to the integration of Mailjet SMS with other platforms or applications, such as integration ID, integration type, and integration status.
Overall, Mailjet SMS's API provides comprehensive access to data related to SMS messaging, enabling users to track and optimize their SMS campaigns for maximum effectiveness.
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:
