Migrating from Magento 2 is one of the most complex technical challenges in today's e-commerce landscape. Its EAV (Entity-Attribute-Value) data model scatters catalog information across dozens of tables with store-level inheritance, turning a simple extraction into a data engineering exercise. To address these complexities, many companies turn to custom applications that enable designing efficient and scalable extraction pipelines.
The first step involves understanding the structure: orders are stored in classic relational tables (sales_order, sales_order_address, sales_order_payment), easy to join with JOINs. However, the product catalog requires a more sophisticated approach. Attribute identifiers (attribute_id), which vary between installations, must be materialized, and then a fallback strategy between the global value (store_id=0) and the store-specific one must be applied. To do this, SQL queries must use COALESCE and multiple LEFT JOINs on tables such as catalog_product_entity_varchar, catalog_product_entity_int, and catalog_product_entity_decimal, with composite indexes on (entity_id, attribute_id, store_id) to avoid production locks.
Once the CSV files with flattened data are generated, the next challenge is to ingest them into the new system without loss or duplicates. A professional Node.js pipeline must handle streaming with backpressure, controlled batch sizes, retries with exponential backoff, and a dead-letter queue. Idempotency via ON CONFLICT DO UPDATE allows resuming the process after any interruption. This architecture directly benefits from the infrastructure of AWS and Azure cloud services, which offer elastic scalability and high availability to process catalogs of hundreds of thousands of products.
Beyond migration, the extracted data can feed artificial intelligence systems and AI agents that optimize prices, recommend products, or automate business decisions. The cybersecurity of the process—from the database connection to cloud storage—is critical, especially when handling sensitive customer information. Likewise, business intelligence tools such as Power BI allow visualizing catalog performance and detecting anomalies after migration. At Q2BSTUDIO, we combine all these capabilities: we develop custom applications for extraction, integrate AI for businesses in subsequent processes, and secure the infrastructure with best security practices. If you are planning a migration from Magento, a professional approach like the one described will save you weeks of work and ensure the integrity of your data.
