DynamoDB vs Memcached: Database or Cache?

Use DynamoDB to store durable application records, and use Memcached to cache data that can be rebuilt after eviction or failure. Memcached can reduce read latency and database load, but it is not a direct substitute for DynamoDB's query, transaction, and recovery capabilities. A common design uses DynamoDB as the source of truth and Memcached for frequently requested records or computed responses.

DynamoDB vs Memcached: an overview

Amazon DynamoDB is a managed key-value and document database. It provides durable storage, managed replication, indexes, conditional writes, transactions, and backup options. You choose keys and capacity settings; AWS runs the underlying storage infrastructure.

Memcached is a distributed memory object cache. Applications store opaque values under keys, often serialized results from a database query or API call. It has a deliberately small interface rather than a document query engine. The official site lists release 1.6.45, dated July 9, 2026, at this article's update.

Memcached can be self-hosted or used through Amazon ElastiCache. Distinguish ElastiCache's serverless and node-based deployments: the managed service can add capabilities that the upstream daemon does not provide by itself.

Comparison at a glance

Shared features and important differences

Both systems provide key-based reads and writes and can be used in latency-sensitive applications. Both require sensible key design and resource planning. Their storage contracts are different: a cache miss is expected behavior in Memcached, while DynamoDB is intended to retain an item until an operation or configured expiration removes it.

Memcached does not understand the fields inside a serialized JSON value. To retrieve a result by customer and by email, the application must maintain separate cache keys or another lookup layer. DynamoDB can model alternate access paths using indexes, with the associated storage and write charges.

The Memcached protocol includes operations such as add, delete, increment, and compare-and-swap (CAS). CAS can reject an update when a cached value changed after you read it. It does not turn several independent keys into an atomic transaction or preserve a value after eviction.

Latency and performance

DynamoDB

DynamoDB is designed for low-latency key-based access. Query and Scan have different work profiles, so compare the operation your application actually uses. A poorly selective filter is not an index. Hot keys, retries, network placement, and item size can dominate application latency.

DynamoDB Accelerator (DAX) caches compatible database reads. It is worth evaluating when you need a DynamoDB-aware cache and do not want to manage an independent cache-key model. It is not a universal multiplier for every read and write.

Memcached

Memcached serves data from its cache without running a database query or recomputing a response. That can help read-heavy pages, API responses, and derived objects. Its user guide describes the basic pattern: check the cache, fetch from the original source on a miss, then cache the result.

Measure the hit ratio and miss penalty together. If most requests miss, the cache adds a network call before the database read. Large values also increase network traffic and serialization work, and a high aggregate request rate says little about the behavior of one overloaded key or server.

Avoid generic requests-per-second promises. Benchmark the chosen client, payload distribution, concurrent connections, and network path. Include a cold-cache run and a node-loss scenario so the database's fallback capacity is visible.

Availability and durability

DynamoDB manages replication across Availability Zones, and global tables add multi-Region replication with consistency choices. Backups and recovery protect against different problems from replication, including application mistakes.

Upstream Memcached does not provide database-style replication between its ordinary cache servers. Losing a server can lose its cached contents. Spreading keys across nodes reduces how much of the cache one failure affects, but the application must still tolerate misses.

ElastiCache Serverless for Memcached is different. AWS documents a replicated Multi-AZ architecture for serverless caches, while node-based Memcached clusters do not support replication. Do not apply a statement about one deployment type to all Memcached installations.

Even a replicated cache can evict or expire data. Keep an authoritative source for records the business cannot lose, and make that source able to absorb a controlled increase in misses.

Security

DynamoDB uses IAM and resource-based policies, encryption at rest, and HTTPS access. VPC endpoints can restrict the network path. Choose permissions for the operations the application needs, rather than granting general administrative access.

Memcached supports TLS when built and configured for it, and SASL authentication through its binary-protocol mechanism. Neither means every installed daemon is automatically authenticated and encrypted. Client compatibility and deployment configuration matter.

The configuration guide covers listening interfaces, connections, and resource settings. Bind to intended interfaces and restrict network access. For ElastiCache, check the security capabilities of the actual engine and deployment mode rather than assuming Redis-oriented controls apply unchanged to Memcached.

Scalability and expiration

DynamoDB on-demand capacity manages request capacity; provisioned mode sets read and write capacity explicitly and optionally uses auto scaling. Both can be limited by concentrated keys or quotas. Scaling the table does not guarantee that an arbitrarily busy item can absorb all traffic.

Memcached clients commonly distribute keys across a server pool. Current Memcached also offers a built-in proxy for routing. Changing the pool can move keys to different servers and increase misses, so plan cache warmup and connection behavior. There is no universal forty-node maximum for the open-source software.

Memcached expiration is also easy to misconfigure. In the standard protocol, an expiration up to 30 days is interpreted as a relative duration; a larger value is interpreted as a Unix timestamp. Zero disables time-based expiration, but does not prevent eviction or loss. Confirm how your client library converts its expiration argument.

DynamoDB TTL instead uses a numeric Unix epoch timestamp for an item. Cleanup is asynchronous, so expired records can remain readable until deleted. Applications must check expiration themselves when it controls authentication or another correctness-sensitive decision.

Backups and restore

DynamoDB supports on-demand backups and point-in-time recovery with a configurable 1-to-35-day window. Restoring creates a new table; recovery also requires reconnecting the application and dependent services.

Upstream Memcached's warm restart can preserve a cache across compatible clean restarts. Its documentation explicitly says this does not make Memcached crash-safe. Flash storage extends cache storage capabilities but should not be mistaken for a durable database backup system.

ElastiCache Serverless for Memcached supports snapshots and restore. These managed snapshots can seed a new cache. They do not change an application's obligation to handle expired entries and misses.

A script that enumerates cache keys and fetches values is not a consistent database backup. Prefer rebuilding from the source of truth or using the documented snapshot feature for a supported managed deployment.

Pricing

DynamoDB pricing combines storage with requests or provisioned throughput, plus applicable index, replication, and backup costs. The pricing calculator helps estimate the read cost that caching might avoid.

Memcached has no software license fee, but hosting is not free. Include memory, compute, networking, monitoring, and operational time. ElastiCache pricing distinguishes node-based charges from serverless storage and compute charges, with minimum metering rules that matter for small caches.

A cache is financially useful when avoided database work or computation justifies its cost and complexity. Estimate savings using the expected hit rate, then measure it after deployment. Cache invalidation failures and an overloaded fallback database are operational costs too.

When to use each, or both

Use DynamoDB for orders, account records, device state, game progress, or shopping carts that must survive loss of a cache. Use Memcached for rendered pages, API responses, database results, and other values that can be reconstructed. Store sessions only when the product can tolerate losing their cached state or has an authoritative backing store.

For DynamoDB plus Memcached, use cache-aside with explicit invalidation:

1. Read the cache using a stable, namespaced key.
2. On a miss, read DynamoDB and fill the cache with a bounded lifetime.
3. After updating DynamoDB, delete or refresh the cached value.
4. Use request coalescing or rate limiting so simultaneous misses do not overload DynamoDB.
5. Monitor hit ratio, evictions, database throttling, and cache errors together.

DynamoDB Streams can drive asynchronous invalidation, but introduces delay and retry handling. For strict read-after-write behavior, bypass the cache or use an application versioning strategy. Do not promise strong consistency merely because DynamoDB can provide a strong read on a cache miss.