Amazon RDS for PostgreSQL vs RabbitMQ

Overview

Amazon RDS for PostgreSQL

Stacks814

Followers607

Votes40

RabbitMQ

Stacks21.8K

Followers18.9K

Votes558

GitHub Stars13.2K

Forks4.0K

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

<Write Introduction here>

Deployment and Management: Amazon RDS for PostgreSQL is a fully managed service that handles database deployment, patch management, and backups automatically. On the other hand, RabbitMQ is a messaging broker that requires manual deployment and configuration, leading to a higher maintenance overhead.
Data Persistence: Amazon RDS for PostgreSQL provides persistent storage for relational data, ensuring data durability and availability. In contrast, RabbitMQ is focused on message routing and delivery rather than data persistence, making it more suitable for ephemeral messaging tasks.
Data Structure: In Amazon RDS for PostgreSQL, data is structured in tables and follows the relational database model, enabling complex querying and transactions. RabbitMQ, however, uses queues and exchanges for message routing, lacking the relational features of a traditional database like PostgreSQL.
Data Scaling: Amazon RDS for PostgreSQL offers horizontal scaling through read replicas and vertical scaling with different instance sizes, allowing for increased performance and capacity. In contrast, RabbitMQ scaling is primarily achieved through clustering multiple nodes, which can be more complex to manage and scale compared to RDS.
Use Cases: Amazon RDS for PostgreSQL is well-suited for applications requiring structured data storage, complex queries, and transactional support. On the other hand, RabbitMQ is ideal for applications with high message throughput, asynchronous communication, and the need for decoupling components in a distributed system.
Integration Capabilities: Amazon RDS for PostgreSQL can integrate with various AWS services like Lambda, S3, and Redshift, enabling seamless data workflows within the AWS ecosystem. RabbitMQ, on the other hand, offers integrations with different programming languages and frameworks, making it more versatile for integrating messaging capabilities into diverse systems.

In Summary, Amazon RDS for PostgreSQL and RabbitMQ differ in deployment and management, data persistence, structure, scaling options, use cases, and integration capabilities.

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Advice on Amazon RDS for PostgreSQL, RabbitMQ

viradiya

Apr 12, 2020

Needs adviceon

AngularJS

ASP.NET Core

MSSQL

We are going to develop a microservices-based application. It consists of AngularJS, ASP.NET Core, and MSSQL.

We have 3 types of microservices. Emailservice, Filemanagementservice, Filevalidationservice

I am a beginner in microservices. But I have read about RabbitMQ, but come to know that there are Redis and Kafka also in the market. So, I want to know which is best.

933k views933k

Comments

Pulkit

Software Engineer

Oct 30, 2020

Needs adviceon

Django

Amazon SQS

RabbitMQ

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

Software engineer at Digital Science

Sep 24, 2020

Needs adviceon

ZeroMQ

RabbitMQ

Amazon 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

Detailed Comparison

Amazon RDS for PostgreSQL	RabbitMQ
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.	RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
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	Robust messaging for applications;Easy to use;Runs on all major operating systems;Supports a huge number of developer platforms;Open source and commercially supported
Statistics
GitHub Stars -	GitHub Stars 13.2K
GitHub Forks -	GitHub Forks 4.0K
Stacks 814	Stacks 21.8K
Followers 607	Followers 18.9K
Votes 40	Votes 558
Pros & Cons
Pros 25 Easy setup, backup, monitoring 13 Geospatial support 2 Master-master replication using Multi-AZ instance	Pros 235 It's fast and it works with good metrics/monitoring 80 Ease of configuration 60 I like the admin interface 52 Easy to set-up and start with 22 Durable Cons 9 Too complicated cluster/HA config and management 6 Needs Erlang runtime. Need ops good with Erlang runtime 5 Configuration must be done first, not by your code 4 Slow

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

Kafka

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

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.

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.

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

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

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

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

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

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

<Write Introduction here>

Deployment and Management: Amazon RDS for PostgreSQL is a fully managed service that handles database deployment, patch management, and backups automatically. On the other hand, RabbitMQ is a messaging broker that requires manual deployment and configuration, leading to a higher maintenance overhead.
Data Persistence: Amazon RDS for PostgreSQL provides persistent storage for relational data, ensuring data durability and availability. In contrast, RabbitMQ is focused on message routing and delivery rather than data persistence, making it more suitable for ephemeral messaging tasks.
Data Structure: In Amazon RDS for PostgreSQL, data is structured in tables and follows the relational database model, enabling complex querying and transactions. RabbitMQ, however, uses queues and exchanges for message routing, lacking the relational features of a traditional database like PostgreSQL.
Data Scaling: Amazon RDS for PostgreSQL offers horizontal scaling through read replicas and vertical scaling with different instance sizes, allowing for increased performance and capacity. In contrast, RabbitMQ scaling is primarily achieved through clustering multiple nodes, which can be more complex to manage and scale compared to RDS.
Use Cases: Amazon RDS for PostgreSQL is well-suited for applications requiring structured data storage, complex queries, and transactional support. On the other hand, RabbitMQ is ideal for applications with high message throughput, asynchronous communication, and the need for decoupling components in a distributed system.
Integration Capabilities: Amazon RDS for PostgreSQL can integrate with various AWS services like Lambda, S3, and Redshift, enabling seamless data workflows within the AWS ecosystem. RabbitMQ, on the other hand, offers integrations with different programming languages and frameworks, making it more versatile for integrating messaging capabilities into diverse systems.

In Summary, Amazon RDS for PostgreSQL and RabbitMQ differ in deployment and management, data persistence, structure, scaling options, use cases, and integration capabilities.

Amazon RDS for PostgreSQL vs RabbitMQ

Overview