Table Storage does not allow any other indexes other than the main primary ones (Row Key and Partition Key). You also cannot store complex object within fields and use them in a query. You basically just serialize the data and stuff it into the field.
The dynamic schema is very nice if you can leverage it but the actually query support is TERRIBLE. (Sorry Microsoft, I'm a fanboy but you blew it here). There is no Order By or event Count support which makes a lot of things very difficult. Want to know how many "color=green" records there are? Guess what, you're going to retrieve all those rows and then count them yourself. They're starting to listen to the community and have just recently introduced upserts and projection (select). I would love to see them adopt something like MongoDB instead :)
For more issues check out: http://www.mygreatwindowsazureidea.com/forums/34192-windows-...
Edit - For what its worth. We've moved more things to SQL Azure now that it has Federation support. Scalability with the power of SQL. http://blogs.msdn.com/b/windowsazure/archive/2011/12/13/buil...
Your partition keys can be composite, have a look here:
I agree with your other pain points - in terms of not being able to get counts, secondary indices etc. However, you can easily simulate some of those - maintain your own summary tables, indices and so on. These ought to emerge as platform features pretty soon though. It's not perfect, but its feature set is close to Dynamo.
As for Mongo DB, I guess this service has been built from ground-up to provide the availability guarantees and automatic partition management features. I don't know if Mongo provides those. You could run Mongo yourself on Azure if you wanted to; there's even a supported solution done recently.
• They both are NoSQL schema-less table stores, where a table can store entities with completely different properties
• They have a two attribute (property) composite primary key.One property that is used for partitioning and the other property is for optimizing range based operations within a partition
• Both of them have just a single index based on their composite primary key
• Both are built for effectively unlimited table size, seamlessly auto scale out with hands off management
• Similar CRUD operations
How Windows Azure Tables is implemented can be found in this SOSP paper and talk:
As mentioned by someone else, one difference is that DynamoDB stores its data completely in SSDs, whereas, in Azure Storage our writes are committed via journaling (to either SSD or a dedicated journal drive) and reads are served from disks or memory if the data page is cached in memory. Therefore, the latency for single entity small writes are typically below 10ms due to our journaling approach (described in the above SOSP paper). Then single entity read times for small entities are typically under 40ms, which is shown in the results here:
Once and awhile we see someone saying that they see 100+ms latencies for small single entity reads and that is usually because they need to turn Nagle off, as described here:
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