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While this loads — worth knowing
ElastiCache RedisnotElastiCache Memcached
Redis has data structures — sorted sets, counters, pub/sub. Memcached has plain keys and nothing else.
Loading…
While this loads — worth knowing
Redis has data structures — sorted sets, counters, pub/sub. Memcached has plain keys and nothing else.
A queue between the part of your system that creates work and the part that does it, so a slow or broken consumer never costs you the work.
Where SQS takes you7 steps, all open
Some parts of a system make work faster than other parts can finish it. In a flash sale a shop takes orders far quicker than its warehouse system can book them. Wire the two together directly and the slow side sets the pace of the fast side, or drops orders when it falls over.
SQS sits between them. The producer sends a message and moves on. Consumers take messages when they are ready. If every consumer is down for an hour, the orders wait in the queue instead of disappearing: a message is kept for 4 days by default, and for up to 14.
Waiters clip tickets onto a rail and walk away. A cook takes one, and while it is being cooked nobody else can see it. The plate goes out and the ticket goes in the bin. If the cook walks out halfway through, the ticket goes back on the rail after a while for someone else. A ticket that has come back three times goes to the manager, because something about that order is wrong.
QueueSendMessageReceiveMessageVisibilityTimeoutDeleteMessagemaxReceiveCountChangeMessageVisibility, before the timeout runs out..fifoThe API answers the customer the moment the order is in the queue. Workers in an Auto Scaling group long-poll the queue and write to the database at the pace it can take. A message that is received three times without being deleted moves to the dead-letter queue, where it waits for a person instead of being retried forever. CloudWatch watches the backlog, and the workers scale with it. When a worker is replaced, whatever it had not finished becomes visible again for another worker.
Each worker finishes 20 orders a second. One step of the chart is one second.
The workers keep up. Nothing waits.
A Standard queue has no capacity to provision. What runs out is the consumers, and how you add them depends on what they run on.
Lambda scales for you. The event source mapping starts with five batches at once and adds up to 300 more concurrent invocations a minute while messages keep coming. To stop the functions overwhelming a database behind them, set maximum concurrency on the event source mapping, and keep the function's reserved concurrency at least that high, or Lambda throttles the messages.
Workers in an Auto Scaling group should scale on backlog per instance, not on CPU. A worker waiting on a slow database shows low CPU while the queue grows, so a CPU alarm may never fire.
FIFO gets its parallelism from message groups. Messages in one group are handled in order, one at a time, so more groups means more workers can run at once.
Visibility timeout 30 s, sped up to 6 s here. maxReceiveCount is 3.
maxReceiveCount is how many times a message can be received before it moves to the dead-letter queue. Set it high enough to allow real retries: at 1, a single failure sends a message aside.
Give the dead-letter queue a longer retention than the source queue. A Standard queue's message keeps its original enqueue time when it moves, so in a short-lived dead-letter queue it can expire before anyone looks at it. The dead-letter queue must be in the same account and Region as the source.
Access. IAM policies on your roles say what they may do. A queue policy on the queue itself is what lets another account, or a service such as SNS or S3, send to it.
At rest. SSE-SQS uses keys SQS manages. SSE-KMS uses a key in KMS. When an AWS service such as SNS, S3 or EventBridge sends to a queue encrypted with SSE-KMS, the key must be a customer managed key whose key policy lets that service call kms:GenerateDataKey and kms:Decrypt. The AWS managed key for SQS will not do: its key policy cannot be changed. Get this wrong and the messages never arrive.
In transit. A queue policy condition on aws:SecureTransport refuses any request that is not made over HTTPS.
Private access. A VPC endpoint lets workers in private subnets reach SQS without crossing the internet, and a queue policy can refuse requests that do not come through it.
You pay per request. Every SQS action is a request, and each 64 KB chunk of a payload is billed as one: a 200 KB message costs four requests to send.
Batch. Sending, receiving and deleting up to 10 small messages per call cuts the request count by up to ten.
Long-poll. An empty receive is a request too. Long polling waits up to 20 seconds for messages to arrive instead of asking again and again.
FIFO requests are charged at their own, higher rate. Every account gets 1 million requests a month free.
Data transfer between SQS and your resources in the same Region is free. Across Regions, or to and from the internet, it is billed at the usual AWS rates.
Prices change, so none are printed here. Check the SQS pricing page on aws.amazon.com.
| Service | How it delivers | Who gets a message | Keeps messages | Choose it when |
|---|---|---|---|---|
| SQS | Consumers pull | One consumer per message | Up to 14 days | Work must happen once, at the back end's pace |
| SNS | Pushes to subscribers | Every subscriber gets a copy | No. Retries, then discards it unless a dead-letter queue is attached | One event, many independent receivers |
| EventBridge | Routes by rules on the event's content | Every target whose rule matches | Only in an archive you create, which can replay them | Routing AWS, SaaS and your own events, or running on a schedule |
| Kinesis Data Streams | Consumers read an ordered log per shard | Every consumer reads everything | 24 hours by default, up to 365 days | Ordered, replayable data read by several consumers |
| Amazon MQ | An ActiveMQ or RabbitMQ broker | Depends on queue or topic | Yes, on the broker | Existing JMS, NMS, AMQP, STOMP or MQTT code, unchanged |
must be processed exactly once, in the order receivedA FIFO queue
A Standard queue can deliver a message twice, and out of order.
some messages are processed more than onceRaise the visibility timeout
The work takes longer than the timeout, so the message reappears while the first worker is still on it. Or extend it as you go with ChangeMessageVisibility.
reduce the number of empty responsesLong polling
Set the receive wait time, up to 20 seconds.
each order must reach billing, shipping and analyticsSNS fanning out to one queue each
A single queue hands each message to only one of them.
migrate an application that uses JMS without changing codeAmazon MQ
SQS has its own API. MQ speaks the protocols the application already uses.
one malformed message keeps failingA dead-letter queue
Set maxReceiveCount so it is moved aside for a person to look at.
the payloads are larger than SQS allowsPayload in S3, pointer in the message
The Extended Client Library does this for you, for payloads up to 2 GB. SQS itself takes up to 1 MiB.
scale the EC2 workers that process the queueTarget tracking on backlog per instance
Not CPU. A worker stuck waiting shows low CPU while the queue grows.
A retailer's checkout API sends orders straight to a fulfilment service running on EC2. In a flash sale, orders arrive at ten times the usual rate, the fulfilment service falls behind, and some orders are lost when its instances are replaced. The order in which orders are fulfilled does not matter, but none may be lost, and checkout must keep answering customers in under a second. What should a solutions architect do?
Image uploads arrive in bursts. Each job must be handled by exactly one worker, and a job must survive the worker crashing halfway through. What goes in the gap?
30 s by default, up to 12 h. Shorter than the work means duplicates.4 days by default, from 1 min to 14 days.20 s per receive. Fewer empty responses, a lower bill.maxReceiveCount moves a message that keeps failing out of the way, for a person to look at.1 MiB. Anything bigger goes in S3, with a pointer in the message.This whole page is free right now.The AWS library is still being written, so every page of it is open to everyone while that lasts. It becomes a paid bundle later; what you read today costs you nothing.
Every fact on this page was checked against AWS’s own documentation on 15 Sept 2026. If AWS has changed something since, its page is the one to trust.