Data masking and transformation at the edge: introducing Gluesync field functions

Modern data replication architectures often operate across heterogeneous database systems, where schema definitions and data formats do not always align. Moving data between platforms such as Oracle, PostgreSQL, Couchbase, or SingleStore typically requires handling differences in types, formats, and representations.

Historically, addressing these mismatches required external transformation logic or custom scripts, increasing pipeline complexity and operational overhead.

With Gluesync 2.2.9, this process is simplified through the introduction of Field Functions, a built-in library of transformations available directly within the replication engine.

Configured through the visual Fields Editor, Field Functions allow teams to apply field-level transformations during replication without writing custom Java code.

Before Field Functions, even basic operations, such as converting dates to strings, trimming whitespace, or casting numeric values, often required custom Java User Defined Functions (UDFs. These operations are now available directly within the Control Plane through a no-code interface.

No-code data preparation in the replication pipeline

Field Functions bring data transformation closer to the replication process itself. Managed through the Gluesync Control Plane, they allow users to apply transformations directly to individual fields on a column-by-column basis.

Two execution models are supported:

• regular column transformations: applied to existing source fields during replication. These include operations such as type casting, string trimming, and basic encoding conversions, helping align source data with target schemas.
• technical field transformations: applied to target-only fields that are not present in the source dataset. These are commonly used to enrich replicated records with metadata such as timestamps or static environment values.

Categories of Field Functions

Field Functions include a set of built-in expressions designed to cover common transformation requirements in data replication workflows. They can be grouped into functional categories based on their behavior.

1. Temporal formatting functions

Temporal functions support conversion between date, time, and string formats. Functions such as Date2Str, Time2Str, and OffsetDateTime2Str allow temporal values to be formatted for target systems, including support for ISO-8601 patterns where applicable.

2. String-to-temporal parsing

These functions handle the conversion of string-based values into native temporal types. Examples include Str2Date, Str2Time, and Str2OffsetDateTime, enabling consistent handling of timestamp data from external or legacy sources.

3. Numeric conversion functions

Numeric casting functions simplify type compatibility across heterogeneous systems. Values can be converted between types such as BigDecimal, Integer, Long, Float, and Double without requiring external transformation logic.

4. Text and binary processing

Text processing functions provide basic data sanitization and encoding capabilities. The Trim function removes leading and trailing whitespace, while Bytes2Str and Str2Bytes enable conversion between binary and string representations using configurable encodings.

5. Technical fields and constants

Technical functions allow enrichment of replicated data with generated or static values. Functions such as LocalTs and OffsetTs can append timestamps, while constant functions such as ConstInt and ConstStr insert fixed values into target fields.

6. Date and time transformations

Additional temporal functions support timezone-aware conversions and format adaptations between different date and time representations. Functions such as OffsetDateTime2Date and DateTime2OffsetDateTimeWithZone help ensure consistency across systems with different temporal requirements.

7. Data masking and anonymization

To comply with data governance policies and privacy regulations (such as GDPR or PCI-DSS), Gluesync allows sensitive production data to be obfuscated or pseudonymized in transit before it is committed to target systems or data lakes. This category provides cryptographic and character-level masking tools configured via the no-code dropdown:

• MaskString: partially replaces characters in a text field with a masking character (such as *), preserving only a specified number of visible trailing or leading elements. It requires defining three parameters in the UI: the target string field, the mask character, and the number of characters to leave exposed.
  • Example: Masking a credit card number string 1234567812345678 into ************5678.
• HashString: replaces sensitive plain text with an irreversible cryptographic hash, making it ideal for anonymizing unique identifiers while preserving data distribution and statistical analysis capabilities. It requires selecting the source field and the hashing algorithm (such as SHA-256).
  • Example: Transforming a clear-text email address user@company.com into its unique 64-character SHA-256 hex signature.

Visual configuration in the Fields Editor

Field Functions are configured directly within the Gluesync Control Plane through the Fields Editor.

1. Open an active replication pipeline in the Objects Browser and navigate to the Fields tab
2. Select the source column or define a target-only technical field
3. Open the Field Function selector for the chosen field
4. Choose the required transformation from the available expressions
5. Provide optional parameters if required (such as formatting patterns or timezones)
6. Save the configuration to apply changes to the pipeline.

Simplifying transformation logic in replication pipelines

By integrating transformation capabilities directly into the replication layer, Field Functions reduce the need for external processing scripts and simplify pipeline design.

This allows teams to manage data transformations centrally within Gluesync while maintaining consistency across heterogeneous environments.

For complete reference of available Field Functions, visit our official Gluesync Documentation Hub.

Field Functions are available as part of Gluesync 2.2.9 and can be used across supported deployment environments including cloud, virtualized infrastructure, and Kubernetes-based systems.

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