Traditional data storage methods, such as plain Parquet files, are susceptible to partial failures during write operations. This can result in incomplete data files and a lack of clear recovery options in the event of a system crash.

Delta Lake’s write operation with ACID transactions helps solve this by:

• Ensuring either all data is written successfully or none of it is
• Maintaining a transaction log that tracks all changes
• Providing time travel capabilities to recover from failures

Here’s an example showing Delta Lake’s reliable write operation:

from deltalake import write_deltalake, DeltaTable
import pandas as pd

initial_data = pd.DataFrame({
    "id": [1, 2],
    "value": ["a", "b"]
})

write_deltalake("customers", initial_data)

If the append operation fails halfway, Delta Lake’s transaction log ensures that the table remains in its last valid state.

try:
    # Simulate a large append that fails halfway
    new_data = pd.DataFrame({
        "id": range(3, 1003),  # 1000 new rows
        "value": ["error"] * 1000
    })

    # Simulate system crash during append
    raise Exception("System crash during append!")
    write_deltalake("customers", new_data, mode="append")

except Exception as e:
    print(f"Write failed: {e}")

    # Check table state - still contains only initial data
    dt = DeltaTable("customers")
    print("\nTable state after failed append:")
    print(dt.to_pandas())

    # Verify version history
    print(f"\nCurrent version: {dt.version()}")

Output:

Write failed: System crash during append!

Table state after failed append:
   id value
0   1     a
1   2     b

Current version: 0

Link to Delta Lake.