DynamoDB DAX vs Global Tables
| Feature | DynamoDB DAX | DynamoDB Global Tables |
|---|---|---|
| Purpose | In-memory caching for low-latency reads | Multi-region replication for low-latency access globally |
| Performance Focus | Speeds up read-heavy workloads | Ensures low-latency access across regions |
| Latency | Microseconds for cached reads | Milliseconds (based on network latency and consistency) |
| Data Replication | No replication (caches only in-memory near application) | Replicates data across multiple regions |
| Write Operations | No impact on writes | Multi-master writes supported |
| Consistency | Cache may return stale data temporarily | Eventual or strong consistency supported |
| Use Case | Accelerating local reads and hot partitions | Ensuring low-latency, multi-region access to data |
| Disaster Recovery | Not applicable | Provides built-in disaster recovery |
| Scalability | Cluster-based caching with managed scaling | Scales globally with DynamoDB automatic scaling |
| Setup Complexity | Easy to set up for caching | Requires configuration for multi-region tables |
| Cost | Additional cost for DAX cluster | Charges for replication and data transfer between regions |
When to Use DAX vs Global Tables
Use DAX When:
- You have read-heavy workloads where the same data is queried frequently.
- You need ultra-low-latency responses (microseconds) for read operations.
- Your application is localized to a single region, and caching can improve performance for hot data.
- You want a managed caching layer to reduce the load on DynamoDB.
Use Global Tables When:
- Your architecture demands data replication across regions without building custom solutions.
- You have a globally distributed user base requiring low-latency access to data from multiple regions.
- You need fault tolerance and disaster recovery across regions.
- Your application requires multi-region writes and eventual consistency.
