How to load data from TrustPilot to Convex

Learn how to use Airbyte to synchronize your TrustPilot data into Convex within minutes.

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Building in-house pipelines

Bespoke pipelines are:
  • Inconsistent and inaccurate data
  • Laborious and expensive
  • Brittle and inflexible
Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.

After Airbyte

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  • Reliable and accurate
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  • Deployed and governed your way
All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and AI Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a TrustPilot connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Convex for your extracted TrustPilot data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the TrustPilot to Convex in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

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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.

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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.

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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

Tech Lead at Symend

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

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Chase Zieman

Chief Data Officer

“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.”

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Rupak Patel

Operational Intelligence Manager

"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."

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How to Sync to Manually

Step 1: Export Data from Trustpilot

Start by logging into your Trustpilot account. Navigate to the "Reviews" section, where you can manage your reviews. Use the export function to download your data, typically in a CSV format. This file will contain all necessary details like review text, author, date, and rating.

Step 2: Prepare the Data for Transformation

Open the exported CSV file using spreadsheet software like Excel or Google Sheets. Review the data to ensure it is complete and accurate. Remove any unnecessary columns and format the data to suit the structure required by Convex, ensuring headers are labeled appropriately for ease of transformation.

Step 3: Cleanse and Standardize Data

Perform data cleansing to ensure consistency and quality. This may include removing duplicates, fixing typos, and standardizing the data format (e.g., consistent date formats, capitalizing names consistently). This step is crucial to prevent errors during the import process into Convex.

Step 4: Format Data for Convex Import

Convert the cleansed data into a format that Convex can accept. Typically, this involves saving the spreadsheet in a CSV or JSON format. Check Convex’s data import requirements or guidelines to ensure compatibility, such as specific data fields and data types they require.

Step 5: Access Convex Database

Log in to your Convex account and navigate to the database section where you intend to import the data. If necessary, create a new database or table that matches the structure of your prepared data to ensure seamless integration.

Step 6: Manually Import Data into Convex

Use Convex’s import function to manually upload your prepared CSV or JSON file. Follow the prompts to map your data fields correctly to the respective fields in Convex. Ensure you verify that each data field aligns correctly to prevent errors.

Step 7: Verify and Validate Imported Data

After the import process is complete, review the data in Convex to ensure it imported correctly. Conduct spot checks to compare the source data from Trustpilot with the data now in Convex. Validate data integrity, such as correct values and formatting, to confirm a successful data migration.

By following these steps, you can effectively move your data from Trustpilot to Convex manually, ensuring data accuracy and integrity without relying on third-party connectors or integrations.