# How do you handle transactional integrity during data loading?

Source: https://zilliz.com/ai-faq/how-do-you-handle-transactional-integrity-during-data-loading
Author: zilliz

To handle transactional integrity during data loading, you must ensure operations adhere to ACID principles (Atomicity, Consistency, Isolation, Durability). Start by wrapping the entire data load process in a database transaction. This ensures *atomicity*: if any part of the load fails, the transaction rolls back, leaving the system in its original state. For example, if you’re inserting 10,000 records and an error occurs on record 5,000, the transaction ensures no partial data is committed. Tools like SQL’s `BEGIN TRANSACTION`, `COMMIT`, and `ROLLBACK` are foundational here. For large datasets, batch processing within smaller transactions (e.g., committing every 1,000 rows) can balance atomicity with performance, allowing partial progress while minimizing rollback overhead.

Next, enforce *consistency* by validating data before or during the load. Use database constraints (e.g., unique keys, foreign keys) or application-level checks to ensure incoming data meets requirements. For instance, if loading customer orders, verify that customer IDs exist in the `customers` table before inserting orders. Temporarily disabling constraints during bulk loads (e.g., using `ALTER TABLE DISABLE CONSTRAINT`) can speed up ingestion, but re-enable them afterward to validate all data. Alternatively, use staging tables: load data into a temporary table, validate it, then merge it into the target table in a transaction. This isolates validation from production data and avoids blocking live operations.

Finally, manage *isolation* and *durability* by controlling how the load interacts with concurrent operations. Use database isolation levels (e.g., `READ COMMITTED` or `SERIALIZABLE`) to prevent conflicts with other transactions. For example, a `SERIALIZABLE` level ensures no phantom reads occur during the load. For durability, ensure the database’s write-ahead log (WAL) or recovery mechanism is configured to persist changes once committed. Tools like PostgreSQL’s `COPY` command or SQL Server’s `BULK INSERT` with `TABLOCK` can optimize performance while maintaining isolation. Always test rollback scenarios and monitor locks to avoid deadlocks or long-running transactions that degrade system responsiveness.