StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Utilities
  3. Background Jobs
  4. Message Queue
  5. Amazon RDS for PostgreSQL vs Amazon SQS

Amazon RDS for PostgreSQL vs Amazon SQS

OverviewDecisionsComparisonAlternatives

Overview

Amazon SQS
Amazon SQS
Stacks2.8K
Followers2.0K
Votes171
Amazon RDS for PostgreSQL
Amazon RDS for PostgreSQL
Stacks814
Followers607
Votes40

Amazon RDS for PostgreSQL vs Amazon SQS: What are the differences?

Amazon RDS for PostgreSQL and Amazon SQS are two different AWS services with distinct functionalities. In this comparison, we will focus on highlighting the key differences between these two services.
  1. Data Storage vs Message Queueing: The primary difference between Amazon RDS for PostgreSQL and Amazon SQS lies in their core functionalities. RDS for PostgreSQL is a managed relational database service that provides storage and retrieval of structured data, while SQS is a fully managed message queuing service that enables decoupling of components in distributed systems.

  2. Data Persistence vs Data Transmission: Another major difference is in how these services handle data. RDS for PostgreSQL provides durable storage for data and allows users to write, read, and modify the data directly. On the other hand, SQS enables message transmission between different components, allowing for asynchronous and reliable communication.

  3. Structured Data vs Unstructured Messages: RDS for PostgreSQL focuses on storing and retrieving structured data in a tabular format, making it ideal for transactional and analytical workloads. In contrast, SQS handles unstructured messages, allowing developers to pass messages between systems without the need for tight coupling.

  4. Database Management vs Event-driven Communication: RDS for PostgreSQL provides a managed database environment, taking care of backups, patching, and scalability. It is suitable for scenarios where data consistency and database management are critical. SQS, on the other hand, facilitates event-driven communication between distributed systems, making it ideal for asynchronous and loosely coupled architectures.

  5. Real-time Data Access vs Delayed Processing: With RDS for PostgreSQL, data can be accessed and modified in real-time, ensuring immediate consistency for applications relying on up-to-date data. In contrast, SQS operates asynchronously, allowing for delayed message processing and reducing dependencies between different components.

  6. Scaling Constraints: When it comes to scaling, RDS for PostgreSQL provides vertical scaling where users can increase the compute and storage capacity of a database instance. In contrast, SQS offers horizontal scalability, allowing users to handle increased message traffic by adding more message queues or leveraging features like message sharding.

In summary, Amazon RDS for PostgreSQL focuses on data storage and retrieval, providing a managed relational database service. On the other hand, Amazon SQS enables asynchronous and reliable message transmission, facilitating decoupling and event-driven communication in distributed systems.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Advice on Amazon SQS, Amazon RDS for PostgreSQL

Pulkit
Pulkit

Software Engineer

Oct 30, 2020

Needs adviceonDjangoDjangoAmazon SQSAmazon SQSRabbitMQRabbitMQ

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.

474k views474k
Comments
Meili
Meili

Software engineer at Digital Science

Sep 24, 2020

Needs adviceonZeroMQZeroMQRabbitMQRabbitMQAmazon SQSAmazon SQS

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}|tool:1064| 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

500k views500k
Comments
Lonnie
Lonnie

CEO - Co-founder US, Mexico Binational Tech Start-up Accelerator, Incubator at Framework Science

May 9, 2019

ReviewonAmazon DynamoDBAmazon DynamoDBAmazon RDS for PostgreSQLAmazon RDS for PostgreSQL

We use Amazon RDS for PostgreSQL because RDS and Amazon DynamoDB are two distinct database systems. DynamoDB is NoSQL DB whereas RDS is a relational database on the cloud. The pricing will mainly differ in the type of application you are using and your requirements. For some applications, both DynamoDB and RDS, can serve well, for some it might not. I do not think DynamoDB is cheaper. Right now we are helping Companies in Silicon Valley and in Southern California go SERVERLESS - drastically lowering costs if you are interested in hearing how we go about it.

9.18k views9.18k
Comments

Detailed Comparison

Amazon SQS
Amazon SQS
Amazon RDS for PostgreSQL
Amazon RDS for PostgreSQL

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 RDS manages complex and time-consuming administrative tasks such as PostgreSQL software installation and upgrades, storage management, replication for high availability and back-ups for disaster recovery. With just a few clicks in the AWS Management Console, you can deploy a PostgreSQL database with automatically configured database parameters for optimal performance. Amazon RDS for PostgreSQL database instances can be provisioned with either standard storage or Provisioned IOPS storage. Once provisioned, you can scale from 10GB to 3TB of storage and from 1,000 IOPS to 30,000 IOPS.

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.
Monitoring and Metrics –Amazon RDS provides Amazon CloudWatch metrics for you DB Instance deployments at no additional charge.;DB Event Notifications –Amazon RDS provides Amazon SNS notifications via email or SMS for your DB Instance deployments.;Automatic Software Patching – Amazon RDS will make sure that the PostgreSQL software powering your deployment stays up-to-date with the latest patches.;Automated Backups – Turned on by default, the automated backup feature of Amazon RDS enables point-in-time recovery for your DB Instance.;DB Snapshots – DB Snapshots are user-initiated backups of your DB Instance.;Pre-configured Parameters – Amazon RDS for PostgreSQL deployments are pre-configured with a sensible set of parameters and settings appropriate for the DB Instance class you have selected.;PostGIS;Language Extensions :PL/Perl, PL/pgSQL, PL/Tcl;Full Text Search Dictionaries;Advanced Data Types : HStore, JSON;Core PostgreSQL engine features
Statistics
Stacks
2.8K
Stacks
814
Followers
2.0K
Followers
607
Votes
171
Votes
40
Pros & Cons
Pros
  • 62
    Easy to use, reliable
  • 40
    Low cost
  • 28
    Simple
  • 14
    Doesn't need to maintain it
  • 8
    It is Serverless
Cons
  • 2
    Has a max message size (currently 256K)
  • 2
    Difficult to configure
  • 2
    Proprietary
  • 1
    Has a maximum 15 minutes of delayed messages only
Pros
  • 25
    Easy setup, backup, monitoring
  • 13
    Geospatial support
  • 2
    Master-master replication using Multi-AZ instance

What are some alternatives to Amazon SQS, Amazon RDS for PostgreSQL?

Kafka

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

RabbitMQ

RabbitMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Celery

Celery

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.

NSQ

NSQ

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

ActiveMQ

ActiveMQ

Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.

ZeroMQ

ZeroMQ

The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.

Apache NiFi

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

Gearman

Gearman

Gearman allows you to do work in parallel, to load balance processing, and to call functions between languages. It can be used in a variety of applications, from high-availability web sites to the transport of database replication events.

Heroku Postgres

Heroku Postgres

Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.

Memphis

Memphis

Highly scalable and effortless data streaming platform. Made to enable developers and data teams to collaborate and build real-time and streaming apps fast.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase