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  4. Message Queue
  5. ActiveMQ vs Heroku Postgres

ActiveMQ vs Heroku Postgres

OverviewDecisionsComparisonAlternatives

Overview

ActiveMQ
ActiveMQ
Stacks879
Followers1.3K
Votes77
GitHub Stars2.4K
Forks1.5K
Heroku Postgres
Heroku Postgres
Stacks607
Followers314
Votes38

ActiveMQ vs Heroku Postgres: What are the differences?

ActiveMQ: A message broker written in Java together with a full JMS client. 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; Heroku Postgres: Heroku's Database-as-a-Service. Based on the most powerful open-source database, PostgreSQL. Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.

ActiveMQ belongs to "Message Queue" category of the tech stack, while Heroku Postgres can be primarily classified under "PostgreSQL as a Service".

"Open source" is the top reason why over 9 developers like ActiveMQ, while over 27 developers mention "Easy to setup" as the leading cause for choosing Heroku Postgres.

ActiveMQ is an open source tool with 1.51K GitHub stars and 1.05K GitHub forks. Here's a link to ActiveMQ's open source repository on GitHub.

According to the StackShare community, Heroku Postgres has a broader approval, being mentioned in 74 company stacks & 39 developers stacks; compared to ActiveMQ, which is listed in 33 company stacks and 17 developer stacks.

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Advice on ActiveMQ, Heroku Postgres

Jorge
Jorge

Jan 15, 2020

Needs advice

Considering moving part of our PostgreSQL database infrastructure to the cloud, however, not quite sure between AWS, Heroku, Azure and Google cloud. Things to consider: The main reason is for backing up and centralize all our data in the cloud. With that in mind the main elements are: -Pricing for storage. -Small team. -No need for high throughput. -Support for docker swarm and Kubernetes.

51.8k views51.8k
Comments

Detailed Comparison

ActiveMQ
ActiveMQ
Heroku Postgres
Heroku Postgres

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.

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

Protect your data & Balance your Load; Easy enterprise integration patterns; Flexible deployment
High Availability;Rollback;Dataclips;Automated Health Checks
Statistics
GitHub Stars
2.4K
GitHub Stars
-
GitHub Forks
1.5K
GitHub Forks
-
Stacks
879
Stacks
607
Followers
1.3K
Followers
314
Votes
77
Votes
38
Pros & Cons
Pros
  • 18
    Easy to use
  • 14
    Open source
  • 13
    Efficient
  • 10
    JMS compliant
  • 6
    High Availability
Cons
  • 1
    Low resilience to exceptions and interruptions
  • 1
    ONLY Vertically Scalable
  • 1
    Support
  • 1
    Difficult to scale
Pros
  • 29
    Easy to setup
  • 3
    Dataclips for sharing queries
  • 3
    Extremely reliable
  • 3
    Follower databases
Cons
  • 2
    Super expensive
Integrations
No integrations available
PostgreSQL
PostgreSQL
Heroku
Heroku

What are some alternatives to ActiveMQ, Heroku Postgres?

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.

Amazon SQS

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

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.

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.

Amazon RDS for PostgreSQL

Amazon RDS for PostgreSQL

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.

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.

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