This page provides you with instructions on how to extract data from Webhooks and load it into Azure SQL Data Warehouse. (If this manual process sounds onerous, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
What are webhooks?
A webhook is a way for one application to provide other applications with real-time information. Webhooks send data through user-defined HTTP POST callbacks, which means an application that uses webhooks can POST data when an event occurs to a specified endpoint (web address).
What is Azure SQL Data Warehouse?
Azure SQL Data Warehouse is a cloud-based petabyte-scale columnar database service with controls to manage compute and storage resources independently. It offers encryption of data at rest and dynamic data masking to mask sensitive data on the fly, and it integrates with Azure Active Directory. It can replicate to read-only databases in different geographic regions for load balancing and fault tolerance.
Getting data out of webhooks
Different applications have different ways to set up webhooks. Often, you can use a management console to define the webhook and specify the endpoint to which you want data delivered. You must make sure that the specified endpoint exists on your server.
What does webhook data look like?
Webhooks post data to your specified endpoints in JSON format. It's up to you to parse the JSON objects and decide how to load them into your data warehouse.
Loading data into Azure SQL Data Warehouse
SQL Data Warehouse provides a multi-step process for loading data. After extracting the data from its source, you can move it to Azure Blob storage or Azure Data Lake Store. You can then use one of three utilities to load the data:
- AZCopy uses the public internet.
- Azure ExpressRoute routes the data through a dedicated private connection to Azure, bypassing the public internet by using a VPN or point-to-point Ethernet network.
- The Azure Data Factory (ADF) cloud service has a gateway that you can install on your local server, then use to create a pipeline to move data to Azure Storage.
From Azure Storage you can load the data into SQL Data Warehouse staging tables by using Microsoft's PolyBase technology. You can run any transformations you need while the data is in staging, then insert it into production tables. Microsoft offers documentation for the whole process.
Keeping data from webhooks 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 have to keep an eye on any changes your applications make to the data they deliver. You should also watch out for cases where your script doesn't recognize a new data type. And since you'll be responsible for maintaining your script, every time your users want slightly different information, you'll have to modify the script.
Other data warehouse options
Azure SQL Data Warehouse 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, Snowflake, or Panoply, which are RDBMSes that use similar SQL syntax. 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 Snowflake, and To Panoply.
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 Webhooks to Azure SQL Data Warehouse automatically. With just a few clicks, Stitch starts extracting your Webhooks data via the API, structuring it in a way that is optimized for analysis, and inserting that data into your Azure SQL Data Warehouse data warehouse.