In my experience, cloud is affordable especially for bursty edge cases. They only get unaffordable for hobbyists when you run them 24/7 or have significant amou

In my experience, cloud is affordable especially for bursty edge cases. They only get unaffordable for hobbyists when you run them 24/7 or have significant amounts of traffic, which is really expensive. But since the pricing is public (https://cloud.google.com/pricing/#pricing https://cloud.google.com/pricing/#pricing), we can check. Please double-check my calculations, I may have made a mistake somewhere. * "single 8-core Google Compute Engine (GCE) instance with a 2TB SSD persistent disk ... downloaded the books to the instance’s local disk" Unfortunately doesn't say how long it took. A n1-standard-8 instance costs $0.4 per hour without any discounts, plus a neglegible amount for 10 GB OS disk space. A 375 GB local SSD costs $0.113 per hour, so let's assume a total of about $1 per hour. Pretty affordable if you just run it for a day or so. * "ten 16-core High Mem (100GB RAM) GCE instances (160 cores total) to process the books, each with a 50GB persistent SSD root disk" => 500 GB of persistent SSD root disk at $0.17/GB-month would be 85 per month, so about $3 per day for the storage. The instances are about $1 per hour each, so ~$10/hour. Affordable, but can cost a pretty penny if you need to let it run for more than a day. * "single 32-core instance with 200GB of RAM, a 10TB persistent SSD disk, and four 375GB direct-attached Local SSD Disks" $2 per hour for the highmem instance, another ~$2.36/hour for the persistent SSD, plus the local SSDs, for a total of slightly under $5/hour. Again, dirt cheap if you need it for 1-2 hours, expensive if 1-2 hours turn into 10-20. * cloud storage... no infos how much data it was, but $0.02/GB-month for durable reduced availability storage (which seems like a reasonable choice). For 10 TB, that would be ~$7/day ($200/month). There are additional costs for writing and access: 100,000 "Class A" operations (e.g. writes) cost $1, so that'll be likely at least another $35 for writing the files. Class B operations (reads) cost 1/10th of the price. * traffic - inbound and internal is free, so likely neglegible if you just want to analze a lot of data. However, getting the full data set out would likely be very expensive. $0.12/per GB quickly adds up - 1 TB would be $120, 10 TB would be ~$1110! OTOH, if you just need 100 GB of results out, that's $12. All in all, I'd say that "a couple hundred bucks" is a pretty reasonable assumption, which is still affordable for dedicated hobbyists (I just looked up the price of Märklin model locomotives, which also cost a couple hundred). Especially considering that you get $300 of free trial quota if you sign up - if you're fast, you may even be able to run this for free. BigQuery pricing is highly dependent on what you query, but I'd call $5 per TB of data queried affordable (i.e. for $5, you can run 10 queries over a 100 GB dataset, and only the columns you touch in your query actually count against the amount of data). And the performance is just insane.