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ELT & CDC
Knowledge Base

Monitoring - Data Type Changes - Redshift

Please refer to this page to view the data type mappings from your source to Redshift. If the data type mapping differs on the Redshift side, the following section explains how these changes will be handled by the automatic replication feature.

Original Data Type Updated Data Type Data Type Conversion Widening / Narrowing Column properties adjusted Backfill supported
BIGINT INTEGER BIGINT Narrowing ❌ N/A
SMALLINT BIGINT Narrowing ❌ N/A
NUMERIC NUMERIC Widening ✅ ✅
DOUBLE_PRECISION NUMERIC Widening ✅ ✅
REAL NUMERIC Widening ✅ ✅
VARCHAR VARCHAR Widening ❌ ✅
Others Same as Updated Data Type - ❌ ❌
INTEGER BIGINT BIGINT Widening ❌ ✅
SMALLINT INTEGER Narrowing ❌ N/A
NUMERIC NUMERIC Widening ✅ ✅
DOUBLE_PRECISION DOUBLE_PRECISION Widening ❌ ✅
REAL NUMERIC Widening ✅ ✅
VARCHAR VARCHAR Widening ❌ ✅
Others Same as Updated Data Type - ❌ ❌
SMALLINT BIGINT BIGINT Widening ❌ ✅
INTEGER INTEGER Widening ❌ ✅
NUMERIC NUMERIC Widening ✅ ✅
DOUBLE_PRECISION DOUBLE_PRECISION Widening ❌ ✅
REAL REAL Widening ❌ ✅
VARCHAR VARCHAR Widening ❌ ✅
Others Same as Updated Data Type - ❌ ❌
NUMERIC BIGINT NUMERIC Widening ✅ ✅
INTEGER NUMERIC Widening ✅ ✅
SMALLINT NUMERIC Widening ✅ ✅
NUMERIC NUMERIC - ✅ N/A
DOUBLE_PRECISION NUMERIC Widening ✅ ✅
REAL NUMERIC Widening ✅ ✅
VARCHAR VARCHAR Widening ❌ ✅
Others Same as Updated Data Type - ❌ ❌
DOUBLE_PRECISION BIGINT NUMERIC Widening ✅ ✅
INTEGER DOUBLE_PRECISION Narrowing ❌ N/A
SMALLINT DOUBLE_PRECISION Narrowing ❌ N/A
NUMERIC NUMERIC Widening ✅ ✅
REAL DOUBLE_PRECISION Narrowing ❌ N/A
VARCHAR VARCHAR Widening ❌ ✅
Others Same as Updated Data Type - ❌ ❌
REAL BIGINT NUMERIC Widening ✅ ✅
INTEGER NUMERIC Widening ✅ ✅
SMALLINT REAL Narrowing ❌ N/A
NUMERIC NUMERIC Widening ✅ ✅
DOUBLE_PRECISION DOUBLE_PRECISION Narrowing ❌ N/A
VARCHAR VARCHAR Widening ❌ ✅
Others Same as Updated Data Type - ❌ ❌
VARCHAR VARCHAR VARCHAR - ✅ N/A
Others Same as Updated Data Type - ❌ ❌
DATE VARCHAR VARCHAR Widening ❌ ✅
TIMESTAMP_WITH_TIMEZONE TIMESTAMP_WITH_TIMEZONE Widening ❌ ✅
TIMESTAMP_WITHOUT_TIMEZONE TIMESTAMP_WITHOUT_TIMEZONE Widening ❌ ✅
Others Same as Updated Data Type - ❌ ❌
TIMESTAMP_WITH_TIMEZONE VARCHAR VARCHAR Widening ❌ ✅
DATE TIMESTAMP_WITH_TIMEZONE Narrowing ❌ N/A
TIMESTAMP_WITHOUT TIMEZONE TIMESTAMP_WITH_TIMEZONE Narrowing ❌ N/A
Others Same as Updated Data Type - ❌ ❌
TIMESTAMP_WITHOUT TIMEZONE VARCHAR VARCHAR Widening ❌ ✅
DATE TIMESTAMP_WITHOUT TIMEZONE Narrowing ❌ N/A
TIMESTAMP_WITH TIMEZONE TIMESTAMP_WITH TIMEZONE Widening ❌ ✅
Others Same as Updated Data Type - ❌ ❌
TIME_WITH TIMEZONE VARCHAR VARCHAR Widening ❌ ✅
Others Same as Updated Data Type - ❌ ❌

Important Notes

  • Narrowing Changes: The pipeline will ignore narrowing changes to ensure compatibility between old and new data in the destination.
  • Numeric Field Adjustments: In some cases, the pipeline will change the data type of a numeric field to NUMERIC to accommodate both old and new data in the destination.
  • Handling Precision and Scale Limits: With numeric data types, the pipeline will attempt to fit both old and new data into the destination. However, due to constraints on the destination's maximum precision and scale, this may not always be possible. If the data cannot be accommodated, an error will be thrown, prompting a re-sync.
  • Backfilling: Backfilling a column involves copying existing data from the old column to a new column with the updated data type, ensuring that no data is lost during the conversion.

See Also

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