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 ServiceNow customers to synchronize data between a producer instance and one or more consumer instances by replicating records. After activating a producer replication set and subscribing consumer instances, existing records can be seeded from producer to consumer, and ongoing synchronization maintains data consistency by replicating new or changed records.
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This capability is essential for identifying and addressing missing or mismatched records that might occur due to insert failures or inconsistencies after replication. The data comparison feature in IDR helps locate these discrepancies, allowing customers to reseed affected records and restore synchronization.
Key Features
- Identify missing records: Detect records absent from the consumer instance after seeding.
- Detect mismatched records: Compare producer and consumer data to find discrepancies and view differences.
- Reseeding: Correct synchronization issues by reseeding missing or mismatched records from producer to consumer.
- Transformed data comparison: Supports data comparison even when transformations replicate data to different tables, with some limitations on field comparisons due to field type differences or adapter modifications.
- Compatibility: Supports data comparison across different ServiceNow releases with specific compatibility considerations for producer-to-consumer and consumer-to-producer replication directions and replication set types (unidirectional, bidirectional, discrete, with transformations).
Compatibility Details
Data comparison is supported for various replication set types depending on the ServiceNow release versions of producer and consumer instances. For example:
- Producer on Washington DC or later and consumer on Washington DC or later supports all replication sets.
- Producer Washington DC or later with consumer Vancouver supports unidirectional sets but not bidirectional, discrete, or transformed sets.
- Consumer to producer comparison follows similar patterns with certain restrictions on replication set types based on versions.
Limitations
- Journal fields are excluded due to their potentially large size.
- Attachments are not included in comparisons.
- Records from the Sys Audit [sysaudit] table are excluded.
Practical Use for ServiceNow Customers
ServiceNow customers can use the data comparison feature within IDR to quickly identify and troubleshoot replication issues between instances. By creating data comparison requests, they can pinpoint missing or mismatched records and then reseed these records to maintain accurate and synchronized data across their ServiceNow environments. This capability is critical for ensuring data integrity in multi-instance setups and for resolving replication errors efficiently.
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.
- Attachments are not included in data comparisons.
- Sys Audit [sys_audit] table records are excluded from the comparison.