How to load data from Ashby to Convex
Learn how to use Airbyte to synchronize your Ashby 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 Ashby
Start by logging into your Ashby account and navigate to the data export section. Identify the data sets you wish to transfer to Convex. Export these data sets in a common format such as CSV or JSON, which are typically supported for import by other platforms.
Step 2: Review and Clean Exported Data
Once you have exported the data, review the files to ensure they contain the necessary data elements. Clean the data by removing any duplicates or irrelevant information. Ensure the data is formatted correctly and consistently to prevent any issues during the import process.
Step 3: Prepare Convex for Data Import
Log in to your Convex account and navigate to the section where data can be imported. Familiarize yourself with the import requirements of Convex, including any specific data formats, data types, and field mappings.
Step 4: Transform Data to Match Convex Requirements
Using a spreadsheet tool or a script in a programming language such as Python, transform your data to match the structure and field requirements of Convex. This may involve renaming columns, converting data types, or restructuring data into a required format.
Step 5: Test Data Import with a Sample
Before importing the entire data set, perform a test import using a small sample of your data. This allows you to verify that the data imports correctly and that the fields align as expected in Convex. Address any errors or mismatches that occur during this test run.
Step 6: Import Full Data Set into Convex
Once satisfied with the test import, proceed to import the full data set into Convex. Follow the import process as outlined in Convex's documentation, ensuring you select the correct options based on your data’s structure and the findings from your test import.
Step 7: Verify Data Integrity Post-Import
After the import is complete, thoroughly check the data in Convex to ensure it has been imported correctly and that there are no discrepancies. Validate key fields and data points to confirm that the import process was successful and that the data integrity is maintained.
By following these steps, you can efficiently transfer data from Ashby to Convex without relying on third-party connectors or integrations.