Amazon DynamoDBย vsย Amazon SQS

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Amazon DynamoDB
Amazon DynamoDB

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Amazon SQS
Amazon SQS

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Amazon DynamoDB vs Amazon SQS: What are the differences?

What is Amazon DynamoDB? Fully managed NoSQL database service. All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability. With DynamoDB, you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.

What is Amazon SQS? Fully managed message queuing service. 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.

Amazon DynamoDB belongs to "NoSQL Database as a Service" category of the tech stack, while Amazon SQS can be primarily classified under "Message Queue".

Some of the features offered by Amazon DynamoDB are:

  • Automated Storage Scaling โ€“ There is no limit to the amount of data you can store in a DynamoDB table, and the service automatically allocates more storage, as you store more data using the DynamoDB write APIs.
  • Provisioned Throughput โ€“ When creating a table, simply specify how much request capacity you require. DynamoDB allocates dedicated resources to your table to meet your performance requirements, and automatically partitions data over a sufficient number of servers to meet your request capacity. If your throughput requirements change, simply update your table's request capacity using the AWS Management Console or the Amazon DynamoDB APIs. You are still able to achieve your prior throughput levels while scaling is underway.
  • Fully Distributed, Shared Nothing Architecture โ€“ Amazon DynamoDB scales horizontally and can seamlessly scale a single table over hundreds of servers.

On the other hand, Amazon SQS provides the following key features:

  • A queue can be created in any region.
  • The message payload can contain up to 256KB of text in any format. Each 64KB โ€˜chunkโ€™ 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.

"Predictable performance and cost" is the top reason why over 53 developers like Amazon DynamoDB, while over 45 developers mention "Easy to use, reliable" as the leading cause for choosing Amazon SQS.

According to the StackShare community, Amazon DynamoDB has a broader approval, being mentioned in 444 company stacks & 187 developers stacks; compared to Amazon SQS, which is listed in 384 company stacks and 103 developer stacks.

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What is Amazon DynamoDB?

With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.

What is Amazon SQS?

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.
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What are some alternatives to Amazon DynamoDB and Amazon SQS?
Google Cloud Datastore
Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Amazon SimpleDB
Developers simply store and query data items via web services requests and Amazon SimpleDB does the rest. Behind the scenes, Amazon SimpleDB creates and manages multiple geographically distributed replicas of your data automatically to enable high availability and data durability. Amazon SimpleDB provides a simple web services interface to create and store multiple data sets, query your data easily, and return the results. Your data is automatically indexed, making it easy to quickly find the information that you need. There is no need to pre-define a schema or change a schema if new data is added later. And scale-out is as simple as creating new domains, rather than building out new servers.
Amazon S3
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
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
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Decisions about Amazon DynamoDB and Amazon SQS
Doru Mihai
Doru Mihai
Solution Architect ยท | 4 upvotes ยท 453 views
Amazon DynamoDB
Amazon DynamoDB

I use Amazon DynamoDB because it integrates seamlessly with other AWS SaaS solutions and if cost is the primary concern early on, then this will be a better choice when compared to AWS RDS or any other solution that requires the creation of a HA cluster of IaaS components that will cost money just for being there, the costs not being influenced primarily by usage.

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Praveen Mooli
Praveen Mooli
Technical Leader at Taylor and Francis ยท | 11 upvotes ยท 103.7K views
MongoDB Atlas
MongoDB Atlas
Amazon S3
Amazon S3
Amazon DynamoDB
Amazon DynamoDB
Amazon RDS
Amazon RDS
Serverless
Serverless
Docker
Docker
Terraform
Terraform
Travis CI
Travis CI
GitHub
GitHub
RxJS
RxJS
Angular 2
Angular 2
AWS Lambda
AWS Lambda
Amazon SQS
Amazon SQS
Amazon SNS
Amazon SNS
Amazon Kinesis Firehose
Amazon Kinesis Firehose
Amazon Kinesis
Amazon Kinesis
Flask
Flask
Python
Python
ExpressJS
ExpressJS
Node.js
Node.js
Spring Boot
Spring Boot
Java
Java
#Data
#Devops
#Webapps
#Eventsourcingframework
#Microservices
#Backend

We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

To build #Webapps we decided to use Angular 2 with RxJS

#Devops - GitHub , Travis CI , Terraform , Docker , Serverless

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Reviews of Amazon DynamoDB and Amazon SQS
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How developers use Amazon DynamoDB and Amazon SQS
Avatar of Karma
Karma uses Amazon SQSAmazon SQS

In the beginning we thought we wanted to start using something like RabbitMQ or maybe Kafka or maybe ActiveMQ. Back then we only had a few developers and no ops people. That has changed now, but we didn't really look forward to setting up a queuing cluster and making sure that all works.

What we did instead was we looked at what services Amazon offers to see if we can use those to build our own messaging system within those services. That's basically what we did. We wrote some clients in Ruby that can basically do the entire orchestration for us, and we run all our messaging on both SNS and SQS. Basically what you can do in Amazon services is you can use Amazon Simple Notification Service, so SNS, for creating topics and you can use queues to subscribe to these topics. That's basically all you need for a messaging system. You don't have to worry about scalability at all. That's what really appealed to us.

Avatar of Karma
Karma uses Amazon DynamoDBAmazon DynamoDB

For most of the stuff we use MySQL. We just use Amazon RDS. But for some stuff we use Amazon DynamoDB. We love DynamoDB. It's amazing. We store usage data in there, for example. I think we have close to seven or eight hundred million records in there and it's scaled like you don't even notice it. You never notice any performance degradation whatsoever. It's insane, and the last time I checked we were paying $150 bucks for that.

Avatar of Volkan ร–zรงelik
Volkan ร–zรงelik uses Amazon DynamoDBAmazon DynamoDB

zerotoherojs.com โ€™s userbase, and course details are stored in DynamoDB tables.

The good thing about AWS DynamoDB is: For the amount of traffic that I have, it is free. It is highly-scalable, it is managed by Amazon, and it is pretty fast.

It is, again, one less thing to worry about (when compared to managing your own MongoDB elsewhere).

Avatar of CloudRepo
CloudRepo uses Amazon DynamoDBAmazon DynamoDB

We store customer metadata in DynamoDB. We decided to use Amazon DynamoDB because it was a fully managed, highly available solution. We didn't want to operate our own SQL server and we wanted to ensure that we built CloudRepo on high availability components so that we could pass that benefit back to our customers.

Avatar of Brandon Adams
Brandon Adams uses Amazon SQSAmazon SQS

This isn't exactly low-latency (10s to 100s of milliseconds), but it has good throughput and a simple API. There is good reliability, and there is no configuration necessary to get up and running. A hosted queue is important when trying to move fast.

Avatar of Simple Merchant
Simple Merchant uses Amazon SQSAmazon SQS

SQS is the bridge between our new Lambda services and our incumbent Rails applications. Extremely easy to use when you're already using other AWS infrastructure.

Avatar of nrise
nrise uses Amazon DynamoDBAmazon DynamoDB

๋ช‡๋ช‡ ๋กœ๊ทธ๋Š” ํ˜„์žฌ AWS DynamoDB ์— ๊ธฐ๋ก๋˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ฐœ์„ ์„ ํ†ตํ•ด mongodb ๋กœ ์˜ฎ๊ธธ ๊ณ„ํš์„ ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์•„์ฃผ ๊ฐ„๋‹จํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ์Œ“๋Š” ์šฉ๋„๋กœ๋Š” ๋‚˜์˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค. ๋‹ค๋งŒ, ์ฟผ๋ฆฌ๊ฐ€ ์•„์ฃผ ์ œํ•œ์ ์ž…๋‹ˆ๋‹ค. ์‚ฌ์šฉํ•˜๊ธฐ ์ „์— ๋ฐ˜๋“œ์‹œ DynamoDB ์˜ ์ŠคํŽ™์„ ํ™•์ธํ•  ํ•„์š”๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค.

Avatar of Olo
Olo uses Amazon SQSAmazon SQS

Primary message queue. Enqueueing operations revert to a local file-system-based queue when SQS is unavailable.

Avatar of IndiTip
IndiTip uses Amazon SQSAmazon SQS

I can't afford to lose data if Dynamo throttles my writes, so everything goes into a message queue first.

Avatar of HyperTrack
HyperTrack uses Amazon DynamoDBAmazon DynamoDB

To store device health records as it allows super fast writes and range queries.

How much does Amazon DynamoDB cost?
How much does Amazon SQS cost?