In our system we are using Azure Table to store a list of commands that needs to be send our clients and persisted until the client is available. Because the number of clients is high (more than 100.000), it would be very expensive to store the list of commands in other resources like Redis Cache or SQL Azure.
From the performance perspective, Azure Table are amazing, very fast even at high throughput when you store a lot of data inside them.
At the first version we done a simple mapping, where we had only one Azure Table for all our clients. For each client, we had a dedicated partition in the table. This works great because Azure Table is partitioned (scale) based on the partition.
There is only a small problem with this approach and is related to maintenance and support. If a support engineering needs to look at the commands of a specific user it will be hard for him to navigate and access the data.
The second approach is to create a different Azure Table for each client. The current documentation specify that we can have as many tables we want under a Storage Account without affecting the performance.
Before doing such a change in our system we decided to run a performance test and see if the performance is impacted in one way or another if we have on one table that is big of 100.000 tables.
We run 3 different scenarios with the same load on Azure Table:
From the performance perspective, Azure Table are amazing, very fast even at high throughput when you store a lot of data inside them.
At the first version we done a simple mapping, where we had only one Azure Table for all our clients. For each client, we had a dedicated partition in the table. This works great because Azure Table is partitioned (scale) based on the partition.
There is only a small problem with this approach and is related to maintenance and support. If a support engineering needs to look at the commands of a specific user it will be hard for him to navigate and access the data.
The second approach is to create a different Azure Table for each client. The current documentation specify that we can have as many tables we want under a Storage Account without affecting the performance.
Before doing such a change in our system we decided to run a performance test and see if the performance is impacted in one way or another if we have on one table that is big of 100.000 tables.
We run 3 different scenarios with the same load on Azure Table:
- One big table with all the commands inside it
- 100.000 empty tables (one per client), were clients only checked if they have commands
- 1000.000 tables (one per client), that had 5 commands for each client
The source of the load were on-premises machine. Don't focus on the base latency, but the different between this 3 different scenarios. When we access Azure Table from Azure environment (like Worker Roles), the latency for a read operation is under 10ms.
Results are express in milliseconds and is the average of multiple runs.
As we can see there is no impact having 100.000 tables under Azure Storage or one. Based on your needs, it might be more simple to have multiple tables, especially when you need to be able to run execute cleanup steps on large amounts on data . Accessing tables partitions and delete row by row will be expensive and time consumption. Deleting a whole Azure Table can be done with only one simple request.
We can even say, based on current results that you have better performance if you use multiple tables and not only one.
We can even say, based on current results that you have better performance if you use multiple tables and not only one.
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