Comparing replicated data between instances in Instance Data Replication
Summarize
Summary of Comparing replicated data between instances in Instance Data Replication
Instance Data Replication (IDR) enables synchronization of data between a producer instance and one or more consumer instances in ServiceNow. After activating a producer replication set and subscribing consumers, existing records are sent through seeding, and ongoing changes are replicated to maintain consistency. The data comparison feature helps identify records that are missing or mismatched after replication, allowing you to reseed them and keep data synchronized.
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Key Features
- Identify missing records: Detect records not present on the consumer instance following seeding.
- Identify mismatched records: Compare data to find discrepancies and view differences between producer and consumer records.
- Reseeding capability: Resend missing or mismatched records from the producer to the consumer to restore synchronization.
- Transformed data comparison considerations:
- Mixed results may occur if data transforms replicate records to different tables on the consumer.
- Fields with differing definitions (e.g., column type/length) or modified by adapters (except Task number adapter) are skipped during comparison.
- Compatibility: Starting with the Washington DC release, data comparison supports bidirectional, discrete, and transformation-configured replication sets on producer or consumer instances, with specific compatibility details depending on release versions involved.
Compatibility Details
Data comparison support varies depending on the release versions of producer and consumer instances:
- Producer to consumer comparisons require Washington DC or later on producer; full support when both producer and consumer run Washington DC or later.
- Consumer to producer comparisons also require Washington DC or later on consumer; full support exists when both are Washington DC or later.
- Some replication set types (e.g., discrete sets, certain bidirectional sets) may not be supported in mixed-release environments.
Limitations
- Journal fields are excluded from data comparisons due to their potentially large size.
- Records from the Sys Audit [sysaudit] table are not included in comparisons.
Practical Usage for ServiceNow Customers
ServiceNow customers can use the IDR data comparison feature to ensure data integrity across instances by:
- Running data comparison requests to find and analyze missing or mismatched records between producer and consumer instances.
- Reseeding identified records to maintain synchronized data across environments, which is crucial for consistent business operations.
- Understanding compatibility and limitations to plan replication strategies effectively, especially in multi-instance or multi-release environments.
Find missing or mismatched records by comparing replication data between instances in Instance Data Replication (IDR).
IDR synchronizes data between a producer instance and one or more consumer instances. After you activate a producer replication set and subscribe at least one consumer, you can send existing records from the producer to the consumer by seeding records. After seeding is finished, IDR maintains data synchronization between the instances by replicating new and changed records from the producer to the consumer.
If an insert fails on the consumer or when producer and consumer records don’t match after replication, you can use the data comparison feature in IDR to find these records and reseed them from the producer to the consumer.
Key benefits
- Identify records missing from the consumer instance after seeding.
- Identify mismatched records and view their differences.
- Keep data synchronized between instances by reseeding records.
Comparing transformed data
- The data comparison can return mixed results if records are added to a table on the producer and then a transformation replicates to a different table on the consumer instance.
- Mapped fields with different field definitions are skipped. For example, if a field on the producer has a different column type or column length than the mapped field on the consumer, the field is skipped.
- All fields that are modified by an adapter are skipped except for modifications made by the Task number adapter. For example, if a string is appended using the Concatenate String adapter, the data comparison can't undo the concatenation and compare the data using the original string, so the field is skipped.
Compatibility
Beginning in the Washington DC release, you can compare replicated data in bidirectional replication sets, discrete replication sets, and replication sets with transformations configured on either the producer or the consumer.
| Data comparison | Producer | Consumer | Supported replication sets |
|---|---|---|---|
| Producer to consumer | Washington DC or later | Utah and earlier | None |
| Producer to consumer | Washington DC or later | Vancouver | Supports unidirectional replication sets, but not the following:
|
| Producer to consumer | Washington DC or later | Washington DC or later | All replication sets |
| Data comparison | Consumer | Producer | Supported replication sets |
|---|---|---|---|
| Consumer to producer | Washington DC or later | Utah and earlier | None |
| Consumer to producer | Washington DC or later | Vancouver | Supports bidirectional replication sets, but not the following:
|
| Consumer to producer | Washington DC or later | Washington DC or later | All replication sets, but not unidirectional replication sets |
Limitations
- Journal fields are excluded from the comparison due to the potential size of their content.
- Sys Audit [sys_audit] table records are excluded from the comparison.