Amazon DynamoDB achieves scalability and high availability through several key architectural features and design principles :
Partitioning :
* DynamoDB partitions data across multiple servers based on the partition key.
* Each partition handles a subset of the table's data and throughput.
* Partitioning allows DynamoDB to scale out horizontally, distributing workload across multiple servers and accommodating large volumes of data and high throughput.
Automatic Sharding :
* DynamoDB automatically manages the distribution of data across partitions.
* As the size of the data or the throughput requirements increase, DynamoDB transparently adds more partitions and redistributes data to maintain even workload distribution.
* This automatic sharding process ensures that the system can scale dynamically in response to changing demand without manual intervention.
Replication and Data Durability :
* DynamoDB replicates data across multiple Availability Zones (AZs) within a region for fault tolerance and high availability.
* Each write operation is synchronously replicated to multiple replicas in different AZs to ensure durability.
* In the event of a failure or outage in one AZ, DynamoDB can continue serving requests from replicas in other AZs without data loss.
Consistent Hashing :
* DynamoDB uses consistent hashing to determine which partition a particular item belongs to based on its partition key.
* Consistent hashing ensures that each partition handles a roughly equal share of the data and that the distribution of data remains stable even as partitions are added or removed.
Provisioned Throughput :
* DynamoDB allows users to provision read and write throughput capacity for their tables.
* Throughput capacity is allocated in terms of read capacity units (RCUs) for reads and write capacity units (WCUs) for writes.
* By provisioning throughput capacity based on expected workload, users can ensure that DynamoDB can handle the required read and write throughput without throttling.
Load Balancing and Scaling :
* DynamoDB automatically load balances requests across partitions to evenly distribute workload.
* As the workload increases, DynamoDB can scale out by adding more partitions and adjusting the distribution of data to maintain performance.
* DynamoDB's adaptive capacity feature allows it to handle sudden spikes in traffic by automatically scaling up provisioned throughput capacity to meet demand.
Global Tables :
* DynamoDB Global Tables replicate data across multiple AWS regions for multi-region redundancy and disaster recovery.
* Global Tables enable applications to achieve low-latency access to data from any region while ensuring data consistency and durability across regions.
