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Overview

The TableValidator tool compares data between source and target databases after a migration to verify accuracy. It performs row-by-row comparison using primary key ordering and reports missing rows, extra rows, and value differences.
TableValidator handles database-specific differences automatically, including timestamp normalization, float precision tolerance, trailing space trimming, and NULL/empty string semantics.

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Usage

TableValidator takes a configuration file as its only argument:
The configuration file uses the same key=value format as the orchestrator.

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Required Parameters

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sourceType
string
required
Source database type. Supported values: mysql, mariadb, postgres, oracle, sqlserver, singlestore. (mariadb is accepted as an alias and handled identically to mysql.)
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sourceDsnFile
string
required
Path to a file containing the source database connection string.
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targetType
string
required
Target database type. Supported values: mysql, mariadb, postgres, oracle, sqlserver, snowflake, firebolt, bigquery, databricks, spanner, singlestore, mongodb. (mariadb is accepted as an alias and handled identically to mysql.)
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targetDsnFile
string
required
Path to a file containing the target database connection string.
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schemaFile
string
required
Path to the Wirekite schema file (.skt) generated by the Schema Extractor. Used to determine table structures, column types, and primary keys.
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tablesFile
string
required
Path to a file listing the tables to validate, one per line in schema.table format.

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Optional Parameters

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logFile
string
Path to the log output file. If not specified, output is written to stdout.
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schemaRename
string
Schema mapping for source-to-target name differences. Format: sourceSchema:targetSchema. Use commas for multiple mappings: schema1:mapped1,schema2:mapped2.
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maxThreads
integer
Number of parallel validation threads. Defaults to 2x the number of CPU cores.
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gcpCredfile
string
Path to a GCP service account JSON credentials file. Required when validating against Spanner or BigQuery targets.
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windowSize
integer
default:"100000"
Number of rows per pagination window. The validator uses keyset pagination to compare large tables in chunks of this size.
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stopOnError
boolean
default:"false"
When true, stops validation immediately when any table has differences. When false, continues validating all tables and reports all differences at the end.
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emptyEqualsNull
boolean
default:"false"
When true, treats empty strings and NULL values as equivalent. Useful when migrating from Oracle (which treats empty strings as NULL) to other databases.

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Partial Validation

For large databases, you can validate a random sample instead of all rows:
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samplePercent
integer
default:"0"
Percentage of rows to validate (1-100). When set to 0 (default), all rows are validated.
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sampleRows
integer
default:"0"
Maximum number of rows to validate. When set to 0 (default), all rows are validated. If both samplePercent and sampleRows are set, the smaller sample is used.
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randomizeWindows
boolean
default:"true"
When true, randomly selects which windows to validate during partial validation. When false, validates windows sequentially from the beginning.

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Example Configuration

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Partial Validation Example

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Output

TableValidator reports results per table and provides a summary at the end.

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Per-Table Results

For each table, the validator reports:
  • Source and target row counts
  • Number of rows missing in target
  • Number of extra rows in target
  • Number of rows with value differences
  • Sample rows for each category (up to 10 examples)

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Summary Report

The summary shows totals across all tables:
  • Total tables validated (passed, failed, errors)
  • Total rows compared
  • Total matches, missing, extra, and differences

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Exit Codes

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Comparison Behavior

TableValidator automatically handles common cross-database differences:
You can also run validation through the Web Interface under the Validate tab of a migration.