Reads per $0.01 = (50.60).60 = 180000
Writes per $0.01 = (10.60).60 = 36000
Assuming that you hit your usage is at 100% capacity then from a read prospective DynamoDB is half the price. Writes are much more expensive but many applications are heavily read oriented.
DynamoDB claims single digit millisecond reads, azure tables does not (from my experience.)
Azure tables have a maximum performance over a given partition table of 500 requests per second and over the whole account of 5,000 requests per second. DynamoDB does not state this.
To put this into context:
Assume a system with 5000 writes per second and 50000 reads here are the costs:
AWS Reads: $240
AWS Writes: $120
Aws Total: $360
Azure Reads: $4320
Azure Writes: $432
Azure Total: $4752
Seems like quite a difference for a decent sized read heavy application.
I agree that Dynamo's provisioned throughput capacity is a very useful feature though. Azure does not provide any such performance guarantee; the throughput limit is also a guideline as far as i know, not an absolute barrier.
5000 x 60 x 60 x 24 = 432000000 Writes
50000 x 60 x 60 x 24 = 4320000000 Reads
(432000000/10000) x 0.01 = $432
(4320000000/10000) x 0.01 = $4320
Azure Total Cost For One Days Use: $4752
((5000/10) x 0.01) x 24 = $120
((50000/50) x 0.01) x 24 = $240
AWS Total Cost For One Days Use: $360
You are right that I don't take into account the bulk feature of azure reads & writes but this is down to bulk requests only being possible on a single partition at a time which in my personal experience (not exhaustive) is non-trivial to take advantage of.
If your txns are all within 1KB, your math holds good; otherwise, you pay more. Interesting model, but I suspect it'll average out to similar costs.
For the cost of storage. The base price for Windows Azure Tables is $0.14/GB/month, and the base price for DynamoDB is $1.00/GB/month.
For transactions, there is the following tradeoff
• DynamoDB is cheaper if the application performs operations mainly on small items (couple KBs in size), and the application can’t benefit from batch or query operations that Windows Azure Tables provide
• Windows Azure Tables is cheaper for larger sized entities, when batch transactions are used, or when range queries are used
The following shows the cost of writing or reading 1 million entities per hour (277.78 per second) for different sized entities (1KB vs 64KB). It also includes the cost difference between strong and eventually consistent reads for DynamoDB. Note, Windows Azure Tables allows batch operations and queries for many entities at once, at a discounted price. The cost shown below is the cost per hour for writing or reading 1,000,000 entities per hour (277.78 per second).
• 1KB single entity writes -- Azure=$1 and DynamoDB=$0.28
• 64KB single entity writes -- Azure=$1 and DynamoDB=$17.78
• 1KB batch writes (with batch size of 100 entities) -- Azure=$0.01 and DynamoDB=$0.28
• 64KB batch writes (with batch size of 100 entities) -- Azure=$0.01 and DynamoDB=$17.78
• 1KB strong consistency reads -- Azure=$1 and DynamoDB=$0.05
• 64KB strong consistency reads -- Azure=$1 and DynamoDB=$3.54
• 1KB strong consistency reads via query/scan (assuming 50 entities returned on each request) – Azure=$0.02, DynamoDB=$0.05
• 64KB strong consistency reads via query/scan (assuming 50 entities returned on each request) – Azure=$0.02, DynamoDB=$3.54
• 1KB eventual consistency reads – DynamoDB=$0.028
• 64KB eventual consistency reads – DynamoDB=$1.77