DynamoDB vs ElastiCache: Database or In-Memory Store?

Choose DynamoDB for a managed operational database with indexed item access, conditional writes and transactions. Choose ElastiCache when your application needs in-memory data structures or a cache in front of a database. ElastiCache is no longer exclusively a disposable cache: supported node-based Valkey clusters can enable durability, so compare the actual engine, deployment and durability mode before choosing.

DynamoDB and Amazon ElastiCache: an overview

DynamoDB stores key-value and document items and manages partitioning and replication. Applications use AWS APIs rather than opening a persistent database connection. Keys and indexes determine which requests can be answered efficiently.

Amazon ElastiCache supports Valkey, Redis OSS and Memcached, with Serverless and node-based deployment options. Applications use the selected engine's client protocol and commands. A cached object lookup, a sorted-set leaderboard and an indexed DynamoDB query are different operations, even if each begins with a key.

The first decision is whether the data is authoritative. If a cache entry disappears, can the application recreate it from DynamoDB? If not, a failure and recovery model must be part of the database choice, not an assumption added after launch.

DynamoDB vs ElastiCache at a glance

Latency and performance

DynamoDB

DynamoDB is designed for single-digit millisecond item access. Good key distribution and focused queries matter more than a service-wide headline throughput figure. A scan, a hot partition and a small key lookup have different behavior under load.

A cache can help repeated reads, but calculate its value first. If every request reads a different item, a cache may add a network hop without avoiding many database reads. If requests repeatedly fetch the same product metadata, caching may reduce latency and source traffic substantially.

ElastiCache

In-memory access can reduce latency, especially for small hot values and data-structure operations. End-to-end latency also includes network distance, connection setup, serialization and client behavior. Do not assume that one microsecond figure covers every command or deployment.

Large values and expensive commands can consume disproportionate resources. Test realistic payload sizes, pipelining and concurrency, and include TLS in the production-like benchmark. For durable Valkey clusters, synchronous persistence changes write latency, so compare it separately from ordinary cache writes.

Valkey, Redis OSS or Memcached?

AWS's engine comparison distinguishes the supported options. Memcached fits simple object caching. Valkey and Redis OSS offer richer data structures and replication options, making them useful for counters, sets, leaderboards and other application state.

Engine version matters. Current Valkey releases add capabilities beyond historical Redis OSS deployments, including search features. Check command and client compatibility before migrating an existing workload, and do not assume that features documented for node-based clusters are available in Serverless.

For a leaderboard, storing a precomputed ordered structure in Valkey may fit better than issuing repeated broad database queries. For an order ledger, database correctness and recovery requirements may dominate the latency advantage of an in-memory structure.

Durability, availability and MemoryDB

Traditional ElastiCache caching architectures keep an authoritative copy elsewhere and tolerate cache loss. Replicas and failover improve availability, but they are not automatically a promise that every acknowledged write survives.

ElastiCache durability changes that choice for supported node-based Valkey clusters. Synchronous mode persists writes in a Multi-AZ transactional log before acknowledging them. Asynchronous mode acknowledges first and can lose up to 10 seconds of writes during a failure. The latter trades recovery guarantees for lower write latency.

The durability limitations require Valkey 9.0 or later and supported node types and cluster configuration. Durability is not supported on ElastiCache Serverless. Enable it when creating the cluster; an existing non-durable cluster cannot simply have it switched on.

Amazon MemoryDB is another durable in-memory database with Valkey and Redis OSS compatibility and a Multi-AZ transactional log. Compare supported topology, commands, regional requirements and recovery behavior for the specific service configuration.

DynamoDB remains a different model: persistent items, automatic regional replication and optional global tables. A durable cache-engine deployment is not a drop-in replacement for DynamoDB indexes or transaction APIs.

DAX vs ElastiCache

DynamoDB Accelerator, or DAX, is a DynamoDB-aware cache for eventually consistent reads. It is useful when an application already uses DynamoDB access patterns and repeatedly reads the same items. Strongly consistent reads go to DynamoDB rather than receiving the cached-read acceleration.

ElastiCache gives the application more control over cached values and data structures. You can cache a computed response assembled from several services, rather than only a database item. That flexibility means owning serialization, cache keys, expiration and invalidation logic.

Choose DAX when DynamoDB API compatibility and repeated eligible reads are the main requirements. Choose ElastiCache when you need engine-specific structures or an application cache spanning multiple sources. In either case, define acceptable staleness; a cache does not strengthen the source database's read consistency.

Security

DynamoDB encrypts data at rest and supports IAM policies, resource-based policies and VPC endpoints. Choose AWS owned, AWS managed or customer managed keys according to the required controls and cost.

ElastiCache security depends on engine and deployment. TLS encryption is enabled for Serverless caches, and node-based settings must match supported configurations. At-rest encryption is always enabled for Serverless caches and durability-enabled clusters; node-based Memcached differs from Valkey and Redis OSS.

Configure network access, authentication and authorization together. Reuse secure client connections where appropriate and test certificate handling. IAM permission to manage a cache is not automatically the same thing as permission to read its application data.

Scalability and pricing

DynamoDB on-demand capacity fits variable request volumes, while provisioned capacity can suit predictable traffic. Both require attention to hot keys and quotas. See capacity modes before choosing based only on an idle or peak-hour estimate.

ElastiCache Serverless scales resources without choosing nodes. Node-based clusters expose more topology and sizing decisions. Memory usage, eviction pressure, connection count and command cost remain important in either model. A high cache hit rate does not help if one hot key or expensive operation dominates the service.

ElastiCache pricing charges Serverless workloads for data storage and ElastiCache Processing Units (ECPUs). Node-based deployments charge for provisioned nodes, with reserved options and additional applicable storage or transfer costs. Engine and durability choices can change the estimate.

DynamoDB pricing charges requests or provisioned throughput, storage and optional features. When adding a cache, calculate avoided reads against the entire cache bill and operational complexity. The DynamoDB pricing calculator provides a baseline for that comparison.

Use DynamoDB and ElastiCache together

A cache-aside application checks ElastiCache first, reads DynamoDB on a miss and caches the result with an expiration. Updates must invalidate or replace the cache entry. A DynamoDB Streams consumer can propagate changes, but delivery delay means this remains an asynchronous view.

Design for missed invalidations and concurrent updates. For example, an old read can finish after an invalidation and repopulate stale data. Versioned cache values, bounded TTLs and explicit consistency rules help address that race. Test cache outages and cold starts so a sudden increase in database reads does not overwhelm the source.

Use the authoritative database for decisions that cannot accept stale state, such as checking whether an order was already charged. Cache catalog displays, computed summaries and other reads whose freshness requirements permit it. If ElastiCache is itself the system of record, select and test a durable configuration deliberately.