How to load data from Typeform to DynamoDB
Learn how to use Airbyte to synchronize your Typeform data into DynamoDB 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 Typeform
First, log into your Typeform account and navigate to the form data you wish to export. Use the built-in feature to export your response data in a CSV format. This can typically be done by selecting the form, going to the results or responses section, and choosing the export option. Save the CSV file locally on your computer.
Step 2: Set Up AWS CLI and SDK
Ensure that you have the AWS Command Line Interface (CLI) and AWS SDK installed on your computer. These tools will be used to interact with AWS services. You can install the AWS CLI from the official AWS website and use package managers like pip for Python-based SDKs. Configure the CLI with your AWS credentials using `aws configure`.
Step 3: Create a DynamoDB Table
Log into your AWS Management Console, navigate to DynamoDB, and create a new table. Define the primary key attributes that will uniquely identify your records. For instance, you might use a form response ID or a combination of participant ID and timestamp. Note the table name and key structure for use in later steps.
Step 4: Parse CSV Data
Use a scripting language like Python to parse the exported CSV file. Libraries such as `csv` in Python can help read the CSV data and transform it into a dictionary or JSON format. This transformation is crucial for preparing the data for insertion into DynamoDB, where it needs to be in a JSON-like format.
Step 5: Prepare Data for DynamoDB
Adjust the parsed data to match the schema of your DynamoDB table. Ensure that each data item includes the primary key attributes and any other necessary fields. Convert data types as required by DynamoDB, such as changing number fields to integers or floats and ensuring strings are properly formatted.
Step 6: Write a Script to Insert Data
Use the AWS SDK for your chosen programming language to write a script that inserts data into DynamoDB. For Python, for example, use `boto3` library. The script should iterate over each data item from the parsed CSV and use the `put_item` method to add it to the DynamoDB table. Handle exceptions to manage any errors during insertion, such as duplicate keys or format mismatches.
Step 7: Run and Validate the Data Transfer
Execute your script to transfer the data from the CSV file to DynamoDB. After running the script, validate the data transfer by checking the DynamoDB table through the AWS Management Console. Ensure that all records are correctly inserted and that the data integrity is maintained by comparing a few sample records with the original CSV data.
This guide provides a structured approach to manually transferring data from Typeform to DynamoDB using AWS tools and programming.