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I am designing an app which has a feature that allows a user to store geolocation based data, then later on allow other users to query for those data that falls within a given radius of their current geolocation.

The question is what is the best approach to design the table to be scalable and has great performance? I was thinking of having a table containing latitude as the partition key (pk), longitude as the row key (rk), then an dataid column that maps to another table that uses that dataid as its partition key.

My thinking is that using the 2-way lookup it's going to boost up my performance since both lookup would be instant. Is this the right way of thinking? I was reading somewhere that looking for partition keys that falls into some range is bad. If that is the case how should I approach this? How does Google maps, Apple map kit typically implement those feature?

Willem Van Onsem
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HungryMonkey
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1 Answers1

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This is difficult to answer completely without knowing your access patterns and scenarios fully. You can use the recently published Azure Storage Table design guide to help come up with a good design for your problem

http://azure.microsoft.com/en-us/documentation/articles/storage-table-design-guide/

For reads, Azure Table Storage is designed for fast point queries where client knows the partition key and row key so you need to factor that in your data model. For writes, you want uniform distribution and avoid append/prepend pattern to achieve high scale.

Vinay Shah - Microsoft
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