This page provides you with instructions on how to extract data from FormKeep and load it into PostgreSQL. (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 PostgreSQL?
PostgreSQL, sometimes referred to as Postgres, calls itself "the world's most advanced open source database." The popular object-relational database management system (ORDBMS) offers enterprise-grade features with a strong emphasis on extensibility and standards compliance.
PostgreSQL runs on all major operating systems, including Linux, Unix, and Windows. It's open source, ACID-compliant, and has full support for foreign keys, joins, views, triggers, and stored procedures in multiple languages. PostgreSQL is often employed as a back-end database for web systems and software tools. It's available in cloud-based deployments by most major cloud vendors. And since its syntax forms the basis for querying Amazon Redshift, which makes migration between the two systems relatively painless, Postgres a good tool for developers who may later use Redshift's data warehouse platform.
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.
Loading data into Postgres
Once you have identified all of the columns you will want to insert, you can use the
CREATE TABLE statement in Postgres to create a table that can receive all of this data. Then, Postgres offers a number of methods for loading in data, and the best method varies depending on the quantity of data you have and the regularity with which you plan to load it.
For simple, day-to-day data insertion, running
INSERT queries against the database directly are the standard SQL method for getting data added. Documentation on INSERT queries and their bretheren can be found in the Postgres documentation here.
For bulk insertions of data, which you will likely want to conduct if you have a high volume of data to load, other tools exist as well. This is where the
COPY command becomes quite useful, as it allows you to load large sets of data into Postgres without needing to run a series of INSERT statements. Documentation can be found here.
The Postgres documentation also provides a helpful overall guide for conducting fast data inserts, populating your database, and avoiding common pitfalls in the process. You can find it here.
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
PostgreSQL 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, Snowflake, or Microsoft Azure SQL Data Warehouse, which are RDBMSes that use similar SQL syntax, or Panoply, which works with Redshift instances. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To Redshift, To BigQuery, To Snowflake, To Panoply, and To Azure SQL Data Warehouse.
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 solve this problem automatically. With just a few clicks, Stitch starts extracting your FormKeep data via the API, structuring it in a way that is optimized for analysis, and inserting that data into your PostgreSQL data warehouse.