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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Amazon MQ is a cloud-based managed message broker service that utilizes Apache ActiveMQ, simplifying the process of establishing and running message brokers. These brokers facilitate communication and information exchange between various software systems, which may be built with different programming languages and operate on distinct platforms. By managing the provisioning, setup, and upkeep of ActiveMQ, a widely-used open-source message broker, Amazon MQ significantly eases your operational burden. Integrating your existing applications with Amazon MQ is straightforward, as it supports industry-standard APIs and messaging protocols such as JMS, NMS, AMQP, STOMP, MQTT, and WebSocket. This adherence to standards often eliminates the need to alter existing messaging code when transitioning to AWS. With just a few clicks in the Amazon MQ Console, you can provision your broker while ensuring compatibility with version upgrades, allowing you to utilize the latest version supported by Amazon MQ. After the broker is set up, your applications will be able to seamlessly produce and consume messages, streamlining your workflow and enhancing overall efficiency. Additionally, this service provides scalability, allowing you to adjust resources based on your application's needs, ensuring optimal performance at all times.

Description

Data processing that integrates both streaming and batch operations while being serverless, efficient, and budget-friendly. It offers a fully managed service for data processing, ensuring seamless automation in the provisioning and administration of resources. With horizontal autoscaling capabilities, worker resources can be adjusted dynamically to enhance overall resource efficiency. The innovation is driven by the open-source community, particularly through the Apache Beam SDK. This platform guarantees reliable and consistent processing with exactly-once semantics. Dataflow accelerates the development of streaming data pipelines, significantly reducing data latency in the process. By adopting a serverless model, teams can devote their efforts to programming rather than the complexities of managing server clusters, effectively eliminating the operational burdens typically associated with data engineering tasks. Additionally, Dataflow’s automated resource management not only minimizes latency but also optimizes utilization, ensuring that teams can operate with maximum efficiency. Furthermore, this approach promotes a collaborative environment where developers can focus on building robust applications without the distraction of underlying infrastructure concerns.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

New Relic
AWS App Mesh
AWS CloudFormation
Amazon CloudWatch
CData Connect
DataBuck
Dataplex Universal Catalog
Datasaur
Google Cloud Bigtable
Google Cloud Composer
Google Cloud Datastream
Google Cloud IoT Core
Google Cloud Platform
Google Cloud Profiler
Orchestra
Pantomath
Protegrity
Sedai
Telmai
Ternary

Integrations

New Relic
AWS App Mesh
AWS CloudFormation
Amazon CloudWatch
CData Connect
DataBuck
Dataplex Universal Catalog
Datasaur
Google Cloud Bigtable
Google Cloud Composer
Google Cloud Datastream
Google Cloud IoT Core
Google Cloud Platform
Google Cloud Profiler
Orchestra
Pantomath
Protegrity
Sedai
Telmai
Ternary

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/amazon-mq/

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

cloud.google.com/dataflow

Product Features

Message Queue

Asynchronous Communications Protocol
Data Error Reduction
Message Encryption
On-Premise Installation
Roles / Permissions
Storage / Retrieval / Deletion
System Decoupling

Product Features

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Alternatives

ActiveMQ Reviews

ActiveMQ

Apache Software Foundation

Alternatives

EMQX Reviews

EMQX

EMQ Technologies
Apache Beam Reviews

Apache Beam

Apache Software Foundation