How to load data from Sentry to Firebolt
Learn how to use Airbyte to synchronize your Sentry 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.
Building in-house pipelines
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
After Airbyte
- 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
Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.
Move Large Volumes, Fast
Quickly get up and running with a 5-minute setup that enables both incremental and full refreshes for databases of any size, seamlessly scaling to handle large data volumes. Our optimized architecture overcomes performance bottlenecks, ensuring efficient data synchronization even as your datasets grow from gigabytes to petabytes.
An Extensible Open-Source Standard
More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s AI Connector Builder lets you edit or add new connectors in minutes.
Full Control & Security
Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.
Fully Featured & Integrated
Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.
Enterprise Support with SLAs
Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.
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
Step 1: Export Data from Sentry
Start by exporting the data you want to transfer from Sentry. Sentry does not have a direct export feature, so you will need to use its API to extract data. Identify the data type you need (e.g., events, issues) and use Sentry's REST API to fetch this data. You can perform API calls using tools like `curl` or write a script in Python using the `requests` library to automate this process. Save the extracted data in a structured format, such as CSV or JSON.
Step 2: Transform Data for Compatibility
Once you have the data from Sentry, you may need to transform it to match the schema and data types expected by Firebolt. This step is crucial if there are differences in data formats or if you need to aggregate or cleanse the data. Use a scripting language like Python or data processing tools like Pandas to perform transformations. Convert the data into a format Firebolt can ingest, typically CSV or Parquet.
Step 3: Prepare Firebolt Environment
Before loading the data, ensure that your Firebolt environment is ready to receive it. This involves setting up the necessary database and tables that match the schema of your transformed data. Use the Firebolt console or Firebolt's SQL command-line interface to create the tables with appropriate data types and structures.
Step 4: Upload Transformed Data to Cloud Storage
Firebolt requires data to be available in a cloud storage service before it can be ingested. Upload your transformed data files to a supported cloud storage service, such as Amazon S3. Ensure that the data is stored in a directory structure that matches your intended table layout in Firebolt.
Step 5: Copy Data from Cloud Storage to Firebolt
Use Firebolt's COPY command to transfer data from your cloud storage to Firebolt tables. This command reads the data from the specified cloud storage location and inserts it into the target Firebolt table. You will need to specify the cloud storage credentials and path in the COPY command. Execute this command via the Firebolt SQL editor or command-line interface.
Step 6: Verify Data Integrity
After loading the data, conduct checks to ensure that the data in Firebolt matches the source data from Sentry. Run queries to count rows, check data types, and validate sample records. This step helps ensure that the data transfer was successful and accurate.
Step 7: Automate and Schedule Regular Transfers
If you need to perform this data transfer regularly, automate the steps using scripts. You can schedule these scripts using a cron job on a Unix system or Task Scheduler on Windows. Ensure that the scripts handle errors gracefully and log their activities for troubleshooting purposes.
By following these steps, you can manually transfer and load data from Sentry to Firebolt without relying on third-party connectors or integrations.