Achieving Microsecond Latency with Amazon DynamoDB Accelerator (DAX) - In-Memory Cache Design
Learn about read acceleration for DynamoDB with DAX, cache strategies, and cluster design.
DAX Overview
DAX is an in-memory cache for DynamoDB that reduces read latency from milliseconds to microseconds. Unlike ElastiCache (Redis/Memcached), DAX provides a DynamoDB-compatible API, so migration is completed simply by changing the SDK endpoint to the DAX cluster.
Cache Strategy and Cluster Design
The item cache caches results from GetItem and BatchGetItem, with automatic expiration via TTL (default 5 minutes). The query cache caches result sets from Query and Scan operations. Write-through ensures that the cache is also updated when PutItem or UpdateItem is executed, reducing the risk of stale data on reads. A minimum of 3 nodes (Multi-AZ) is recommended for the cluster, and node type should be selected based on the volume of data to cache.
Cache Strategy and Consistency
DAX manages caching in two layers: item cache and query cache. The item cache holds GetItem and BatchGetItem results with a TTL (default 5 minutes). The query cache holds Query and Scan results. Write operations (PutItem, UpdateItem, DeleteItem) are reflected in both DAX and DynamoDB through write-through. Eventually consistent reads are served from the cache, while strongly consistent reads access DynamoDB directly. There is a trade-off where shorter TTL settings reduce cache hit rates, while longer settings decrease data freshness. For learning about DynamoDB cache performance optimization, related books (Amazon) can be helpful.
DAX Pricing
DAX pricing is based on hourly charges per node. A dax.r5.large costs approximately $0.269 per hour (about $194 per month). A minimum 3-node (Multi-AZ) configuration is recommended, costing approximately $582 per month. Compare the cost savings from reducing DynamoDB Read Capacity Units (RCU) against DAX node costs to determine whether DAX adoption is advantageous for read-heavy workloads. With cache hit rates of 90% or higher, significant RCU reductions can be expected, exceeding the cost of DAX.
Summary
DAX is an in-memory cache for DynamoDB that achieves microsecond-level read latency. It maintains write consistency through write-through caching while significantly reducing read load with two-layer caching of items and queries. The DynamoDB RCU cost reduction effect becomes pronounced at cache hit rates of 90% or higher, making it ideal for read-intensive workloads.