Need advice about which tool to choose?Ask the StackShare community!
Amazon ElastiCache vs Amazon SQS: What are the differences?
Introduction
In this article, we will discuss the key differences between Amazon ElastiCache and Amazon SQS. Both of these services are provided by Amazon Web Services (AWS) and are widely used for different purposes in cloud computing environments.
Elasticity and Scalability: One key difference between Amazon ElastiCache and Amazon SQS is their primary focus. ElastiCache is designed as an in-memory data store service that provides high-performance caching. It is built to seamlessly scale up and down to handle varying workloads efficiently. On the other hand, Amazon SQS is a managed message queuing service that enables decoupling of distributed systems and enhances fault tolerance. It is designed to provide reliable message delivery with scalable and durable message queues.
Data Persistence and Durability: ElastiCache stores data in-memory, which provides extremely fast access times. However, this also means that the data is not inherently persistent, and any data lost due to a cache node failure or reboot is not recoverable. In contrast, Amazon SQS stores messages in a highly durable and reliable manner, ensuring that messages are not lost even if due to system failures or accidental deletion. SQS messages are automatically replicated across multiple availability zones for enhanced durability.
Protocols and Supported Data Types: ElastiCache is compatible with the popular Redis and Memcached protocols, providing support for key-value data stores and facilitating seamless integration with existing applications that use these protocols. Amazon SQS, on the other hand, follows a simple messaging protocol and provides a platform-independent way of exchanging messages between application components. It supports a variety of data types, including strings, numbers, and binary data.
Message Delivery and Order: In Amazon ElastiCache, the data access is typically immediate, as it is stored in-memory within the cache. This allows for extremely low latency and high throughput data retrieval. However, in Amazon SQS, the order of message delivery is not guaranteed, and multiple consumers can receive messages concurrently from the same queue. This makes SQS an ideal choice for applications that require parallel processing or asynchronous communication between components.
Managed Service and Monitoring: ElastiCache is a fully-managed service, meaning that AWS takes care of the underlying infrastructure, patching, and backups. It also provides various monitoring metrics and logs, enabling users to monitor the performance and usage of their cache clusters. Amazon SQS is also a managed service, handling the operational aspects of message queuing. It offers diagnostic and monitoring features, such as CloudWatch metrics and CloudTrail logs, for tracking queue activity and performance.
Use Cases and Prerequisites: ElastiCache is commonly used for improving the performance of applications by caching frequently accessed data, reducing the load on databases, and improving overall response times. It is often used in scenarios that require low-latency data retrieval, such as real-time applications, session stores, and gaming leaderboards. Amazon SQS, on the other hand, is used for building distributed systems and decoupling components to enable fault-tolerant and highly scalable architectures. It is widely used in scenarios involving microservices, event-driven architectures, and background job processing.
In Summary, Amazon ElastiCache and Amazon SQS have key differences in terms of their focus, data persistence, supported protocols, message delivery, management, and use cases. ElastiCache prioritizes high-performance caching with in-memory data storage, while SQS focuses on reliable message queuing with durable message persistence.
Hi! I am creating a scraping system in Django, which involves long running tasks between 1 minute & 1 Day. As I am new to Message Brokers and Task Queues, I need advice on which architecture to use for my system. ( Amazon SQS, RabbitMQ, or Celery). The system should be autoscalable using Kubernetes(K8) based on the number of pending tasks in the queue.
Hello, i highly recommend Apache Kafka, to me it's the best. You can deploy it in cluster mode inside K8S, thus you can have a Highly available system (also auto scalable).
Good luck
Hi, we are in a ZMQ set up in a push/pull pattern, and we currently start to have more traffic and cases that the service is unavailable or stuck. We want to: * Not loose messages in services outages * Safely restart service without losing messages (ZeroMQ seems to need to close the socket in the receiver before restart manually)
Do you have experience with this setup with ZeroMQ? Would you suggest RabbitMQ or Amazon SQS (we are in AWS setup) instead? Something else?
Thank you for your time
ZeroMQ is fast but you need to build build reliability yourself. There are a number of patterns described in the zeromq guide. I have used RabbitMQ before which gives lot of functionality out of the box, you can probably use the worker queues example from the tutorial, it can also persists messages in the queue.
I haven't used Amazon SQS before. Another tool you could use is Kafka.
Both would do the trick, but there are some nuances. We work with both.
From the sound of it, your main focus is "not losing messages". In that case, I would go with RabbitMQ with a high availability policy (ha-mode=all) and a main/retry/error queue pattern.
Push messages to an exchange, which sends them to the main queue. If an error occurs, push the errored out message to the retry exchange, which forwards it to the retry queue. Give the retry queue a x-message-ttl and set the main exchange as a dead-letter-exchange. If your message has been retried several times, push it to the error exchange, where the message can remain until someone has time to look at it.
This is a very useful and resilient pattern that allows you to never lose messages. With the high availability policy, you make sure that if one of your rabbitmq nodes dies, another can take over and messages are already mirrored to it.
This is not really possible with SQS, because SQS is a lot more focused on throughput and scaling. Combined with SNS it can do interesting things like deduplication of messages and such. That said, one thing core to its design is that messages have a maximum retention time. The idea is that a message that has stayed in an SQS queue for a while serves no more purpose after a while, so it gets removed - so as to not block up any listener resources for a long time. You can also set up a DLQ here, but these similarly do not hold onto messages forever. Since you seem to depend on messages surviving at all cost, I would suggest that the scaling/throughput benefit of SQS does not outweigh the difference in approach to messages there.
I want to schedule a message. Amazon SQS provides a delay of 15 minutes, but I want it in some hours.
Example: Let's say a Message1 is consumed by a consumer A but somehow it failed inside the consumer. I would want to put it in a queue and retry after 4hrs. Can I do this in Amazon MQ? I have seen in some Amazon MQ videos saying scheduling messages can be done. But, I'm not sure how.
Mithiridi, I believe you are talking about two different things. 1. If you need to process messages with delays of more 15m or at specific times, it's not a good idea to use queues, independently of tool SQM, Rabbit or Amazon MQ. you should considerer another approach using a scheduled job. 2. For dead queues and policy retries RabbitMQ, for example, doesn't support your use case. https://medium.com/@kiennguyen88/rabbitmq-delay-retry-schedule-with-dead-letter-exchange-31fb25a440fc I'm not sure if that is possible SNS/SQS support, they have a maximum delay for delivery (maxDelayTarget) in seconds but it's not clear the number. You can check this out: https://docs.aws.amazon.com/sns/latest/dg/sns-message-delivery-retries.html
Pros of Amazon ElastiCache
- Redis58
- High-performance32
- Backed by amazon26
- Memcached21
- Elastic14
Pros of Amazon SQS
- Easy to use, reliable62
- Low cost40
- Simple28
- Doesn't need to maintain it14
- It is Serverless8
- Has a max message size (currently 256K)4
- Triggers Lambda3
- Easy to configure with Terraform3
- Delayed delivery upto 15 mins only3
- Delayed delivery upto 12 hours3
- JMS compliant1
- Support for retry and dead letter queue1
- D1
Sign up to add or upvote prosMake informed product decisions
Cons of Amazon ElastiCache
Cons of Amazon SQS
- Has a max message size (currently 256K)2
- Proprietary2
- Difficult to configure2
- Has a maximum 15 minutes of delayed messages only1
Sign up to add or upvote consMake informed product decisions
What is Amazon ElastiCache?
What is Amazon SQS?
Need advice about which tool to choose?Ask the StackShare community!
Sign up to get full access to all the companiesMake informed product decisions
What tools integrate with Amazon ElastiCache?
What tools integrate with Amazon SQS?
Sign up to get full access to all the tool integrationsMake informed product decisions
Blog Posts
+17
+42
+47
+30+26
+23+37+25