Now that Universal Analytics (UA) backups are finally here, we’ve been working hard on getting our client’s data into the cloud to
How much does it really cost to store your data in the cloud?
In this post, we’ll provide readers with a brief guide to Google’s pricing model for BigQuery. We will explain how Google charges for using BigQuery, walk through the free benefits Google Cloud Platform gives on a monthly basis, give examples of how this will apply to clients purchasing a UA backup from BFO, and give a broad example of how to estimate your cost. It is our hope that all readers will walk away with an understanding of how affordable a data warehouse solution with BigQuery actually can be.
Most examples in this article will be aimed towards entry level users. Enterprise clients are encouraged to visit Google’s pricing documentation for a deeper dive into what to expect.
The two components of BigQuery’s pricing to familiarize yourself with are compute pricing and storage pricing. Compute pricing is the cost to process queries and manipulate data to be used for speedy performance with the data visualization software of your choice. Storage pricing is the cost to store the data you load into BigQuery.
Compute pricing with BigQuery is billed at $6.25 per terabyte of data processed per month. Each month, Google gives BigQuery users their first TB of processing for free. For clients purchasing a UA backup, this will come into play when you use your Looker Studio dashboard and when manipulating data with SQL for usage elsewhere.
BigQuery has two different types of storage: active logical storage and long-term storage. Active logical storage is defined as
How does this apply to your Universal Analytics back-up? Well, until you start running SQL queries and building out your own datasets for custom reports, clients who back their data up with BFO will only encounter costs for storage and for when they use their Looker Studio dashboard. Now, each UA backup can be wildly different in size, so it can be difficult to put an exact monthly cost in a blog post. What we can do today is compare our experience to the pricing I’ve just laid out, and leave the rest to your imagination and knowledge of your own business.
BFO is a boutique digital marketing agency. We are small, but don’t be mistaken: we are mighty. And while we certainly don’t have the web traffic of our enterprise clients, we have collected a valuable set of data in our Universal Analytics property. Doing a PDF export of our Looker Studio report queries our entire dataset and comes in just over 250 megabytes. That means I can do that almost 400 times a month before the 1 TB threshold is surpassed and I begin to be charged. And even then, I am starting at $6.25 for the next terabyte, meaning I would have to do some
With each quote we give for a UA backup, we provide an estimated number of total rows the backup will contain. Now, this will vary depending on what sort of data you’ve collected in UA, but our export broke down for roughly 200 MB per 1 million rows of data stored. Now, say you have 500 million rows (this is much more common than you would think), at 200 MB per million rows you would be looking at 100 GB of storage. With your 10 GB of free storage removed, active logical storage comes in at $1.80 per month. Long term storage is half of that, only 90 cents!
As you can see, storing your historical data is actually quite affordable to do with BigQuery. Now, as you build your data warehouse and bring in more information, this will go up, but so will the quality of your reporting! BigQuery is extremely powerful and can be used to open up incredible insights. If you’re not convinced yet, contact BFO for a quote. We’ll be happy to talk you through BigQuery pricing more in order to get you the data you need!