How to load data from Visma Economic to TiDB
Learn how to use Airbyte to synchronize your Visma Economic data into TiDB 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 Visma Economic
Begin by accessing your Visma Economic account. Navigate to the specific modules from which you want to export data (such as invoices, customers, or products). Utilize Visma's built-in export functionality to download the data as CSV or Excel files. Ensure that you export all necessary fields needed for your TiDB database.
Step 2: Prepare the Data for Import
Once you have your data in CSV or Excel format, open the files and review the structure. Ensure that the data is clean and consistent, with no empty fields or corrupted entries. Adjust the column headers to match the schema you plan to use in TiDB. Save the cleaned data in a consistent format, ideally CSV, as it is widely supported for database imports.
Step 3: Set Up Your TiDB Environment
If you haven't already, set up your TiDB database environment. You can do this by installing TiDB locally or using a cloud service that offers TiDB. Follow the official TiDB documentation to set up your database cluster and ensure that it is running correctly.
Step 4: Create the Database Schema in TiDB
Before importing your data, you need to create the appropriate schema in TiDB. Use SQL commands to define the database structure, including tables, columns, data types, and any necessary indexes. Make sure the schema matches the structure of your data from Visma Economic.
Step 5: Import Data into TiDB
Use the `LOAD DATA` SQL command to import your data from the CSV files into TiDB. This can be done via a SQL client connected to your TiDB instance. The command will look something like:
```
LOAD DATA LOCAL INFILE 'path_to_your_file.csv'
INTO TABLE your_table_name
FIELDS TERMINATED BY ','
ENCLOSED BY '"'
LINES TERMINATED BY '\n'
IGNORE 1 LINES;
```
Adjust the command parameters based on the specifics of your CSV file format.
Step 6: Verify Data Integrity
After the data import, run SQL queries to verify that the data has been accurately transferred into TiDB. Check row counts, column data types, and any key fields to ensure data integrity. This step is crucial to confirm that the import process was successful and that the data aligns with the expected format.
Step 7: Optimize and Index Your Data
Once the data is verified, optimize your database for performance by creating necessary indexes and running any optimization queries. Indexing can significantly improve query performance in TiDB, especially for large datasets. Consider your query patterns and index the columns that are frequently used in WHERE clauses or joins.
By following these steps, you can effectively move data from Visma Economic to TiDB without relying on third-party connectors or integrations.