Convex Beta

Convex is a full-stack TypeScript development platform. Replace your database, server functions, and glue code.

NOTE: This connector is partner-built. For any questions related to Convex connector and its documentation, refer to Convex's support team. For details on SLA, see Convex's Status and Guarantees documentation.

Feature Name	Supported	Notes
Capture deletes		All tables and fields
History mode
Custom data
Data blocking		Column level, table level, and schema level Column Hashing
Column hashing
Re-sync		Table level
API configurable		API configuration
Priority-first sync
Fivetran data models
Private networking		AWS Private Link, GCP Private Service Connect
Authorization via API

Setup guide

Follow the step-by-step Convex setup guide to connect your Convex database with Fivetran.

Sync overview

Once Fivetran is connected to your Convex deployment, the connector fetches an initial consistent snapshot of all data from your Convex database. Once the initial sync is complete, the connector uses Change data capture (CDC) to efficiently incrementally sync updates at a newer consistent view of your Convex deployment. You can configure the frequency of these updates.

Configuration

To configure the Convex connector, you need your deployment URL and deploy key. You can find both on your project's Production Deployment Settings page.

Schema information

Fivetran tries to replicate the database and columns from your configured Convex deployment to your destination according to Fivetran's standard database update strategies.

Type transformations and mapping

As the connector extracts your data, it matches Convex data types to types that Fivetran supports.

The following table illustrates how the connector transforms your Convex data types into Fivetran-supported types:

Convex Type	Fivetran Type	Fivetran Supported
Id	STRING	True
Null	NULL	True
Int64	LONG	True
Float64	DOUBLE	True
Boolean	BOOLEAN	True
String	STRING	True
Bytes	BINARY	True
Array	JSON	True
Object	JSON	True

NOTE: The _creationTime system field in each document is special-cased to convert into a UTC_DATETIME, despite being stored as a Float64 inside of Convex.

NOTE: Nested types inside Object and Array are serialized as JSON using the JSON format for export.

Nested data

Convex documents are represented as JSON by using conversions. If the first-level field is a simple data type, the connector will map it to its own type. If it's a complex nested data type such as an array or JSON data, it maps to a JSON type without unpacking. The connector does not automatically unpack nested JSON objects to separate tables in the destination. Any nested JSON objects are preserved as is in the destination so that you can use JSON processing functions.

For example, the following Convex document:

{"street"  : "Main St."
"city"     : "New York"
"country"  : "US"
"phone"    : "(555) 123-5555"
"zip code" : 12345
"people"   : ["John", "Jane", "Adam"]
"car"      : {"make" : "Honda",
              "year" : 2014,
              "type" : "AWD"}
}

is converted to the following table when the connector loads it into your destination:

_id	street	city	country	phone	zip code	people	car
1	Main St.	New York	US	(555) 123-5555	12345	["John", "Jane", "Adam"]	{"make" : "Honda", "year" : 2014, "type" : "AWD"}

Fivetran-generated data

Fivetran adds the following column to every table in your destination:

_fivetran_synced (UTC TIMESTAMP) indicates the time when Fivetran last successfully synced the row. It is added to every table.
_fivetran_deleted (BOOLEAN) indicates if the column was deleted in the source.

Fivetran adds these columns to give you insight into the state of your data and the progress of your data syncs. For more information about these columns, see our System Columns and Tables documentation.