This page provides you with instructions on how to extract data from FormKeep and load it into Snowflake. (If this manual process sounds onerous, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
What is FormKeep?
FormKeep provides form endpoints that designers and developers can use when they don’t want to build and maintain forms themselves.
What is Snowflake?
Snowflake is a cloud-based data warehouse implemented as a managed service. It runs on the Amazon Web Services architecture, and separates compute and storage resources, enabling users to scale the two independently and pay only for resources used. It can provide access to the same data for multiple workgroups or workloads simultaneously with no contention roadblocks or performance degradation.
Getting data out of FormKeep
FormKeep makes its data available through webhooks, which you can set up on FormKeep's Webhooks tab. You provide a URL to send the data to and write your script to POST data to this URL as it's generated.
Preparing FormKeep data
If you don't already have a data structure in which to store the data you retrieve, you'll have to create a schema for your data tables. Then, for each value in the response, you'll need to identify a predefined datatype (INTEGER, DATETIME, etc.) and build a table that can receive them. FormKeep should provide documentation that tells you what fields are provided by each endpoint, along with their corresponding datatypes.
Complicating things is the fact that the records retrieved from the source may not always be "flat" – some of the objects may actually be lists. This means you'll likely have to create additional tables to capture the unpredictable cardinality in each record.
Preparing data for Snowflake
Depending on how your data is structured, you may need to prepare it for loading. Read about the supported data types for Snowflake and make sure that your data maps well to them.
Note that you don't need to define a schema in advance when loading JSON data into Snowflake.
Loading data into Snowflake
Snowflake's documentation outlines a Data Loading Overview that can lead you through the task of loading your data. If you're not loading a lot of data, Snowflake's data loading wizard may be helpful, but for many organizations, its limitations make it unacceptable. Instead, you can:
- Use the PUT command to stage files.
- Use the COPY INTO table command to load prepared data into an awaiting table.
You can copy data from your local drive or from Amazon S3. Snowflake lets you make a virtual warehouse that can power the insertion process.
Keeping FormKeep data up to date
Once you've set up the webhooks you want and have begun collecting data, you can relax – as long as everything continues to work correctly. You'll have to keep an eye out for any changes to FormKeep's webhooks implementation.
Other data warehouse options
Snowflake is great, but sometimes you need to optimize for different things when you're choosing a data warehouse. Some folks choose to go with Amazon Redshift, Google BigQuery, PostgreSQL, or Microsoft Azure Synapse Analytics, which are RDBMSes that use similar SQL syntax, or Panoply, which works with Redshift instances. Others choose a data lake, like Amazon S3 or Delta Lake on Databricks. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To Redshift, To BigQuery, To Postgres, To Panoply, To Azure Synapse Analytics, To S3, and To Delta Lake.
Easier and faster alternatives
If all this sounds a bit overwhelming, don’t be alarmed. If you have all the skills necessary to go through this process, chances are building and maintaining a script like this isn’t a very high-leverage use of your time.
Thankfully, products like Stitch were built to move data from FormKeep to Snowflake automatically. With just a few clicks, Stitch starts extracting your FormKeep data, structuring it in a way that's optimized for analysis, and inserting that data into your Snowflake data warehouse.