Glossary


Glossary


The following table provides a set of standard terms used in the product’s documentation:

Term Definition
APIScript: APIScript is an XML-based language included with CData Sync that can be used to write custom processing logic. APIScript makes it easy to call external processes, allowing users to integrate Sync with other business processes.
Capture Deletes: Sync captures deletes, automatically retrieving a list of deleted records from the source by calling the API or by using the Change Tracking feature.
Change Tracking: Change Tracking is a form of incremental update used when no Last Modified column is available. Change Tracking records information whenever DML statements modify rows in the tracked table. Sync queries the internal change tracking table for records that have changed and updates the destination table accordingly.
Column Mapping: Column Mapping controls how each column in the data source maps to a column in the destination
Connection: A connection is a configured instance of a connector. Connections can include configured settings like user name, password, etc.
Connector: CData Sync comes pre-installed with a select list of popular sources and destinations. In addition, many more connectors are available to download from the CData website.
ELT: ELT (Extract, Load, Transform) is a method of data transformation in which data is moved in its entirety and transformed in the destination.
ETL: ETL (Extract, Transform, Load) is a method of data transformation in which the data is transformed “mid-flight” to the destination. The data is extracted, transformed, then loaded.
Formatters: Formatters support modifying or formatting values within a script. You can use value formatters to perform string, date, and math operations on values.
Incremental Check Column: Incremental Check Column works with most data sources to selectively update only records that have been modified since the last run, using the table’s Last Modified column. Updates by Incremental Check Column can work using two different data types: DateTime Incremental Check Columns and Integer-Based Incremental Check Columns.
Job: Sync jobs are a unit of execution that include the source connection, the destination connection, and a set of one or more Tasks that represent data flows for different tables.
Job History: The Job History table contains the results of every job that has been executed in the past. In addition to the Job History, the execution details of a job are logged to multiple files. The logs can be configured to various levels of verbosity as described below and can be helpful in tracking connectivity errors or troubleshooting other problems in job execution.
Query: A query is a request for a database’s data.
Replicate Interval: Replicate Interval is the time frame into which data is split when it is retrieved during the initial load. This interval is used to batch the updates so that if a failure occurs or the replication is interrupted, the next attempt can pick up where the last run left off. By default, Sync will use 180 days, but you can adjust this to be larger or smaller depending on the amount of data you have and how spread out the data is in terms of time.
Replicate Start Date: In situations where the Min Date is not automatically detected, users can use the Replicate Start Date to set the minimum start date (min date) to begin replicating data. The accepted date format is: (yyyy-MM-dd).
REPLICATE Query: CData Sync manages all transformations in a declarative fashion, using a special purpose SQL command: REPLICATE. The REPLICATE command lets you define the data that is selected, the transformations that are applied, and map the data to a destination table.
Task: Tasks control the data flow from a source into a destination table. In a Standard Replicate Job, all source tables and views are available to be added as Replicate Tasks to the Job.
Transformations: Transformations are a way of transforming, cleansing, or aggregating data in way that makes it easy for reporting or data analysis. In CData Sync, transformations are special types of jobs that execute in the destination after data has been transferred. These jobs can be comprised of any number of SQL statements.