How to load data from Mailjet SMS to Firebolt
Learn how to use Airbyte to synchronize your Mailjet SMS data into Firebolt within minutes.


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

Raman Singh
Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend

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."
How to Sync to Manually
Begin by logging into your Mailjet account. Navigate to the SMS section and locate the data you wish to export. Use Mailjet's export functionality to download the data in a CSV or Excel format. This process will provide you with a file containing all the necessary SMS data.
Open the exported file using a spreadsheet program like Microsoft Excel or Google Sheets. Review the data to ensure it is complete and clean. Remove any unnecessary columns or rows, and standardize the data format to ensure consistency. Save the cleaned data in a CSV format, as this is a compatible format for bulk data loading into most databases.
Access your Firebolt account and navigate to the database where you want to import the SMS data. Ensure that you have the necessary permissions to create tables and load data. If needed, create a new database specifically for this data import, and set up the appropriate schema to match the data structure from your CSV file.
Use the Firebolt SQL editor to create a table that matches the structure of your CSV file. Define the table columns, data types, and any additional constraints or indexes that may be necessary for your analysis. This step ensures that the data can be loaded without errors.
Upload the CSV file to a location accessible by Firebolt, such as an S3 bucket. In Firebolt, use the COPY command to load the data from the CSV file into the newly created table. Specify the file path, data format, and any additional options needed to accurately parse and load the data.
After loading the data, perform a series of checks to ensure data integrity and accuracy. Use SQL queries to compare record counts, spot-check data values, and ensure that no data was lost or altered during the transfer process. This step is crucial to validate that the data in Firebolt matches the original data from Mailjet.
Once the data is successfully loaded and verified, optimize your Firebolt tables for querying. Create necessary indexes to improve query performance and ensure that the data is organized efficiently. This final step prepares your data for analysis and reporting tasks, ensuring that your Firebolt database operates smoothly.