Overview

Functionality
In Feast, each batch data source is associated with a corresponding offline store. For example, a SnowflakeSource can only be processed by the Snowflake offline store. Otherwise, the primary difference between batch data sources is the set of supported types. Feast has an internal type system, and aims to support eight primitive types (bytes, string, int32, int64, float32, float64, bool, and timestamp) along with the corresponding array types. However, not every batch data source supports all of these types.
For more details on the Feast type system, see here.
Functionality Matrix
There are currently four core batch data source implementations: FileSource, BigQuerySource, SnowflakeSource, and RedshiftSource. There are several additional implementations contributed by the Feast community (PostgreSQLSource, SparkSource, and TrinoSource), which are not guaranteed to be stable or to match the functionality of the core implementations. Details for each specific data source can be found here.
Below is a matrix indicating which data sources support which types.
Text
File
BigQuery
Snowflake
Redshift
Postgres
Spark
Trino
bytes
yes
yes
yes
yes
yes
yes
yes
string
yes
yes
yes
yes
yes
yes
yes
int32
yes
yes
yes
yes
yes
yes
yes
int64
yes
yes
yes
yes
yes
yes
yes
float32
yes
yes
yes
yes
yes
yes
yes
float64
yes
yes
yes
yes
yes
yes
yes
bool
yes
yes
yes
yes
yes
yes
yes
timestamp
yes
yes
yes
yes
yes
yes
yes
array types
yes
yes
no
no
yes
yes
no

Text	File	BigQuery	Snowflake	Redshift	Postgres	Spark	Trino
`bytes`	yes	yes	yes	yes	yes	yes	yes
`string`	yes	yes	yes	yes	yes	yes	yes
`int32`	yes	yes	yes	yes	yes	yes	yes
`int64`	yes	yes	yes	yes	yes	yes	yes
`float32`	yes	yes	yes	yes	yes	yes	yes
`float64`	yes	yes	yes	yes	yes	yes	yes
`bool`	yes	yes	yes	yes	yes	yes	yes
`timestamp`	yes	yes	yes	yes	yes	yes	yes
array types	yes	yes	no	no	yes	yes	no

Last modified 7mo ago