AWS Scaling Serverless Databases
Scaling Serverless Databases
Serverless databases are built for serverless environments.
They can scale up and down quickly.
This is because of DynamoDB's horizontal scalability and minimal latency.
By default, tables in on-demand mode scale read and write throughput depending on previous peaks.
On-Demand capacity instantly doubles the previous traffic peak on a table.
It then uses the latest high as the baseline for the next peak.
DynamoDB will still provide you extra capacity if your new peak is doubled within 30 minutes.
Excessive requests will be throttled in a table or index.
Scaling Serverless Databases Video
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DynamoDB Auto Scalling
DynamoDB auto scaling will keep up with changes in workload.
Auto scaling enhances a table's read and write capacity to manage traffic spikes without throttling.
When traffic slows, auto scaling reduces allocated capacity.
Auto scaling comes in when the workload remains high or low for a few minutes.
On-demand is ideal for serverless applications.
It eliminates the need to supply capacity.
Each read and write action costs money.
The cost of a transaction is immediately represented in the reads and writes executed by that transaction.
Amazon DAX
Amazon DAX stands for Amazon DynamoDB Accelerator.
With Amazon DAX, you can get reduced latency.
Applications like real-time bidding, social gaming, and trading can benefit from DAX.
Related reads:
DynamoDB Pricing for On-Demand CapacityDynamoDB Pricing for Provisioned Capacity
