AWS Lambda vs Amazon S3 vs Amazon SQS: What are the differences?
Introduction
In this comparison, we will highlight the key differences between AWS Lambda, Amazon S3, and Amazon SQS.
Functionality: AWS Lambda is a serverless computing service that allows you to run code without provisioning or managing servers. Amazon S3 is a scalable object storage service that allows you to store and retrieve data. Amazon SQS is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications.
Use Cases: AWS Lambda is often used for handling event-driven tasks, data processing, real-time file processing, and orchestrating workflows. Amazon S3 is ideal for storing large amounts of data, hosting static websites, securing data backups, and enabling content delivery. Amazon SQS is commonly utilized for implementing distributed systems, decoupling application components, processing tasks asynchronously, and scaling microservices.
Execution: AWS Lambda executes code in response to triggers such as changes in data, HTTP requests, or time-based schedules. Amazon S3 acts as a central repository for data storage and retrieval. Amazon SQS facilitates communication between different components by queuing and processing messages asynchronously.
Billing: AWS Lambda is billed based on the number of requests and the duration of code execution. Amazon S3 charges based on the amount of data stored, data transfer, and requests made. Amazon SQS pricing is based on the number of messages processed and the data volume transferred.
Scalability: AWS Lambda automatically scales based on incoming requests, ensuring high availability and performance. Amazon S3 can handle massive amounts of data and traffic without manual intervention. Amazon SQS is designed to scale horizontally to accommodate varying workloads efficiently.
Integration: AWS Lambda can be integrated with various AWS services, third-party APIs, and custom applications. Amazon S3 seamlessly integrates with AWS services, content delivery networks, and data analytics platforms. Amazon SQS supports integration with different AWS services, message processing systems, and microservices architecture.
In Summary, the key differences between AWS Lambda, Amazon S3, and Amazon SQS lie in their functionality, use cases, execution methods, billing structures, scalability features, and integration capabilities.
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When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda .
The short story:
Developer Experience trumps everything.
AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
If you need geographic spread, AWS is lonely at the top.
The setup
Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup.
Everything was on the table. But we crossed out a lot quite quickly:
Pure, uncut, self hosted Kubernetes — way too much complexity
Managed Kubernetes in various flavors — still too much complexity
Zeit — Maybe, but no Docker support
Elastic Beanstalk — Maybe, bit old but does the job
Heroku
Lambda
It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly!
But when do you pick which model?
I chopped that question up into the following categories:
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.
At Joyn we use AWS infrastructures extensively, so we need a wide range of different tools starting from file storage until the health monitoring of our running services. For Smart TV stack we use S3 to mostly store static files (like scripts, styles and html), CloudFront to keep good response times using the cache, Lambda to recognize the TV platform and serve appropriate bundle (except Samsung Tizen platform where application is packaged), CloudWatch to receive alerts in case we have any issues inside of our lambda function.
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.
AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.
Write, read, and delete objects containing from 1 byte to 5 terabytes of data each. The number of objects you can store is unlimited.;Each object is stored in a bucket and retrieved via a unique, developer-assigned key.;A bucket can be stored in one of several Regions. You can choose a Region to optimize for latency, minimize costs, or address regulatory requirements. Amazon S3 is currently available in the US Standard, US West (Oregon), US West (Northern California), EU (Ireland), Asia Pacific (Singapore), Asia Pacific (Tokyo), Asia Pacific (Sydney), South America (Sao Paulo), and GovCloud (US) Regions. The US Standard Region automatically routes requests to facilities in Northern Virginia or the Pacific Northwest using network maps.;Objects stored in a Region never leave the Region unless you transfer them out. For example, objects stored in the EU (Ireland) Region never leave the EU.;Authentication mechanisms are provided to ensure that data is kept secure from unauthorized access. Objects can be made private or public, and rights can be granted to specific users.;Options for secure data upload/download and encryption of data at rest are provided for additional data protection.;Uses standards-based REST and SOAP interfaces designed to work with any Internet-development toolkit.;Built to be flexible so that protocol or functional layers can easily be added. The default download protocol is HTTP. A BitTorrent protocol interface is provided to lower costs for high-scale distribution.;Provides functionality to simplify manageability of data through its lifetime. Includes options for segregating data by buckets, monitoring and controlling spend, and automatically archiving data to even lower cost storage options. These options can be easily administered from the Amazon S3 Management Console.;Reliability backed with the Amazon S3 Service Level Agreement.
A queue can be created in any region.;The message payload can contain up to 256KB of text in any format. Each 64KB ‘chunk’ of payload is billed as 1 request. For example, a single API call with a 256KB payload will be billed as four requests.;Messages can be sent, received or deleted in batches of up to 10 messages or 256KB. Batches cost the same amount as single messages, meaning SQS can be even more cost effective for customers that use batching.;Long polling reduces extraneous polling to help you minimize cost while receiving new messages as quickly as possible. When your queue is empty, long-poll requests wait up to 20 seconds for the next message to arrive. Long poll requests cost the same amount as regular requests.;Messages can be retained in queues for up to 14 days.;Messages can be sent and read simultaneously.;Developers can get started with Amazon SQS by using only five APIs: CreateQueue, SendMessage, ReceiveMessage, ChangeMessageVisibility, and DeleteMessage. Additional APIs are available to provide advanced functionality.
Extend other AWS services with custom logic;Build custom back-end services;Completely Automated Administration;Built-in Fault Tolerance;Automatic Scaling;Integrated Security Model;Bring Your Own Code;Pay Per Use;Flexible Resource Model
Statistics
Stacks
55.1K
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2.8K
Stacks
26.0K
Followers
40.2K
Followers
2.0K
Followers
18.8K
Votes
2.0K
Votes
171
Votes
432
Pros & Cons
Pros
590
Reliable
492
Scalable
456
Cheap
329
Simple & easy
83
Many sdks
Cons
7
Permissions take some time to get right
6
Takes time/work to organize buckets & folders properly
6
Requires a credit card
3
Complex to set up
Pros
62
Easy to use, reliable
40
Low cost
28
Simple
14
Doesn't need to maintain it
8
It is Serverless
Cons
2
Difficult to configure
2
Has a max message size (currently 256K)
2
Proprietary
1
Has a maximum 15 minutes of delayed messages only
Pros
129
No infrastructure
83
Cheap
70
Quick
59
Stateless
47
No deploy, no server, great sleep
Cons
7
Cant execute ruby or go
3
Compute time limited
1
Can't execute PHP w/o significant effort
What are some alternatives to Amazon S3, Amazon SQS, AWS Lambda?
