> For the complete documentation index, see [llms.txt](https://docs.zingg.ai/0.3.4/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zingg.ai/0.3.4/connectors/pipes.md).

# Zingg Pipes

Information on Zingg pipes and their working

Zingg Pipes are an abstraction for a data source from which Zingg fetches data for matching or to which Zingg writes its output. This lets users connect to literally any datastore that has a Spark connector.

The pipe is an easy way to specify properties and formats for the Spark connector of the relevant data source. Zingg pipes can be configured through the config [JSON](/0.3.4/stepbystep/configuration.md) passed to the program by outlining the datastore connection properties.

Pipes can be configured for the data or the output attributes on the [JSON](/0.3.4/stepbystep/configuration.md).

Each pipe has the following attributes:

## name

A unique name to identify the data store.

## format

One of the Spark-supported connector formats. jdbc/avro/parquet etc.

## options

Properties to be passed to spark.read and spark.write.

Let us look at some common data sources and their configurations.