How to load data from Orb to Convex
Learn how to use Airbyte to synchronize your Orb data into Convex 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 Orb
Begin by logging into your Orb account. Navigate to the data export section, typically found under settings or data management. Select the datasets you wish to export. Choose the appropriate file format for export, commonly CSV or JSON, and initiate the export process. Once complete, download the exported file to your local system.
Step 2: Prepare Data for Transfer
Open the exported file using a spreadsheet program (for CSV) or a text editor (for JSON). Review the data to ensure it's in a clean and consistent format. Remove any unnecessary columns or fields that are not needed in Convex. Make sure that the data types and structures align with the requirements of Convex to avoid import issues.
Step 3: Access Convex Database
Log into your Convex account. If you haven't already set up a database within Convex, do so by following their setup instructions. Make sure you have the necessary permissions to create or modify databases and tables, as you will need to import data into the appropriate locations.
Step 4: Create Corresponding Tables in Convex
Using the Convex database interface, create tables that correspond to the datasets you plan to import. Ensure the schema of the tables matches the structure of your data file, including field names and data types. This step is crucial to ensure a smooth import process.
Step 5: Convert Data to SQL Insert Statements
If Convex supports SQL, convert your data into SQL INSERT statements. This involves iterating over each row of your cleaned data file and creating an INSERT statement with the corresponding values. If Convex uses a different query language or API for data insertion, prepare the data accordingly to match that format.
Step 6: Import Data into Convex
Using Convex's database interface or command line tools, execute the prepared SQL INSERT statements or the equivalent queries for data import. If Convex provides a bulk import tool, use it to efficiently upload large datasets. Monitor the import process for any errors and address them as they arise.
Step 7: Verify Data Integrity
Once the data import is complete, verify the integrity of the data within Convex. Run queries to check that all records were imported correctly and that there are no discrepancies. Compare a sample of records from Convex against the original data from Orb to ensure accuracy. Make adjustments as necessary to rectify any issues found.
This guide will help you manually transfer data from Orb to Convex while ensuring data integrity and consistency.