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Version: 1.0.0

PostgreSQL


Replicate your data in minutes, through our UI or programatically with our APIs.

Replicate your PostGreSQL data in minutes#

The Katonic PostgreSQL integration will replicate your PostgreSQL data to your data warehouse or database. Perform analysis on your PostgreSQL data, without the headache of writing and maintaining ETL scripts.

The Postgres source supports both Full Refresh and Incremental syncs. You can choose if this connector will copy only the new or updated data, or all rows in the tables and columns you set up for replication, every time a sync is run.

Check our detailed documentation on how to start syncing your PostGreSQL data.

Features of the Connector#

FeaturesSupported
Full Refresh SyncYes
Incremental SyncYes
Replicate Incremental DeletesComing soon
Logical Replication (WAL)Coming soon
SSL SupportYes
SSH Tunnel ConnectionComing soon

The PostGreSQL source supports Full refresh syncs. That is, every time a sync is run, Katonic will copy all rows in the tables and columns you set up for replication into the destination in a new table.

Resulting schema#

The Postgres source does not alter the schema present in your database. Depending on the destination connected to this source, however, the schema may be altered. See the destination’s documentation for more details.

Data type mapping#

Postgres data types are mapped to the following data types when synchronizing data:

Postgres Type / Resulting Type / Notes

  • bigint / integer
  • bit / boolean
  • boolean / boolean
  • character / string
  • character varying / string
  • cidr / string
  • citext / string
  • date / string
  • double precision / string
  • enum / number
  • hstore / object / may be de-nested depending on - the destination you are syncing into
  • inet / string
  • int / integer
  • json / string
  • jsonb / strong
  • macaddr / string
  • money / string
  • numeric / number
  • real / number
  • smallint / integer
  • text / string
  • time with timezone / string / may be written as a native date type depending on the destination
  • time without timezone / string / may be written as a native date type depending on the destination
  • timestamp with timezone / string / may be written as a native date type depending on the destination
  • timestamp without timezone / string / may be written as a native date type depending on the destination
  • uuid / string

Note: arrays for all the above types as well as custom types are supported, although they may be de-nested depending on the destination. Byte arrays are currently unsupported