Redshift In Dev

The Fivetran Redshift connector allows you to sync tables from your Redshift dataset to your destination. We can sync any number of schemas and tables from within your Redshift database.

TIP: If you want to sync multiple Redshift databases, we recommend that you create a connector for each database.

Features

Feature Name	Supported	Notes
Capture deletes		All tables and fields
History mode
Custom data		All tables and fields
Data blocking		Column level, table level, and schema level
Column hashing
Re-sync		Connector and table level
API configurable		API configuration
Priority-first sync
Fivetran data models
Private networking		AWS PrivateLink

Schema information

Fivetran tries to replicate the exact schema and tables from your Redshift source dataset to your destination.

We name the source schema with the dataset name you provided in the connector setup form. We replicate the source's tables and views to the destination schema. We name the destination schema with the connector name appended by the dataset name. For example, if the connector name is redshift_db and the dataset name is fivetran_schema, the destination schema name is redshift_db_fivetran_schema.

Type transformations and mapping

As we extract your data, we match Redshift data types to types that Fivetran supports. If we don't support a data type, we automatically change that type to the closest supported type or, in some cases, don't load that data at all. Our system automatically skips columns with data types that we don't accept or transform.

The following table illustrates how we transform your Redshift data types into Fivetran-supported types:

Data Type	Fivetran Type	Regular Column Support	Primary Key Support (Teleport)
SMALLINT	SHORT	Yes	Yes
INTEGER	INT	Yes	Yes
BIGINT	LONG	Yes	Yes
DECIMAL	BIGDECIMAL	Yes	No
REAL	BIGDECIMAL	Yes	No
DOUBLE PRECISION	BIGDECIMAL	Yes	No
BOOLEAN	BOOLEAN	Yes	No
CHAR	STRING	Yes	Yes
VARCHAR	STRING	Yes	Yes
DATE	LOCALDATE	Yes	No
TIMESTAMP	LOCALDATETIME	Yes	No
TIMESTAMPTZ	LOCALDATETIME	Yes	No
GEOGRAPHY	JSON	Yes	No
GEOMETRY	JSON	Yes	No
SUPER	STRING	Yes	No
HLLSKETCH	N/A	No	No
TIME	N/A	No	No
TIMETZ	STRING	Yes	No
VARBYTE	BINARY	Yes	No
ARRAY	N/A	No	No
STRUCT	N/A	No	No

Updating data

Fivetran performs incremental updates of any new or modified data from your source database. We use Fivetran Teleport Sync, our proprietary incremental sync method, to fetch only the data that has changed since our last sync. Learn more in our Fivetran Teleport Sync documentation.

NOTE: Teleport captures deletes differently than log-based replication mechanisms. Learn more in our Changes to data between syncs documentation.

Automatic table re-syncs

We do not support DDL operations.

Tables with a primary key

We merge changes to tables with primary keys into the corresponding tables in your destination:

An INSERT in the source table generates a new row in the destination with _fivetran_deleted = FALSE.
A DELETE in the source table updates the corresponding row in the destination with _fivetran_deleted = TRUE.
An UPDATE in the source table updates the data in the corresponding row in the destination.

Tables without a primary key

Fivetran currently does not support Redshift tables without a primary key.