Manage Data in Snowflake with CloverDX

Connecting to Snowflake

CloverDX offers two ways of connecting to Snowflake.

The first way is via a JDBC driver that allows the largest flexibility to run various queries on the target Snowflake instance. The only requirement in this case is a driver that can be downloaded directly from Snowflake’s website and then added to Designer or Server.

The second way – using a custom subgraph-based connector – allows you to connect to your Snowflake instance and perform high-performance bulk data loads that use all the power Snowflake offers.

You can download code below to show you how to create this subgraph.

High-performance Snowflake Data Loads

As an ETL tool for Snowflake, CloverDX offers fast loading of data.

The bulk writer component is implemented as a subgraph (a user-defined component) that performs several operations to load the data into Snowflake instance – it loads the data into staging area in Snowflake, then loads data from the staging area into a table and finally deletes any local temporary files.

This is the fastest way of getting your data to Snowflake, as the data is uploaded to the cloud in parallel in multiple threads. This means Snowflake can run its data loads in parallel as well. As such, this is the best way to load large volumes of data into your warehouse.

Try it yourself

• Get a 45-day CloverDX trial
• Download sample Snowflake project

The sample project shows how to create a CloverDX subgraph (reusable component) that allows you to write data to your Snowflake instance via bulk-write operation (i.e. using PUT and COPY commands). You can use the subgraph to write data to Snowflake instance (included in the example). Additionally, you can compare the performance of writes between the bulk method and regular JDBC connection.