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  5. IBM MQ vs Kafka UI

IBM MQ vs Kafka UI

OverviewComparisonAlternatives

Overview

IBM MQ
IBM MQ
Stacks118
Followers187
Votes11
Kafka UI
Kafka UI
Stacks16
Followers19
Votes0
GitHub Stars11.5K
Forks1.3K

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Detailed Comparison

IBM MQ
IBM MQ
Kafka UI
Kafka UI

It is a messaging middleware that simplifies and accelerates the integration of diverse applications and business data across multiple platforms. It offers proven, enterprise-grade messaging capabilities that skillfully and safely move information.

It is a simple tool that makes your data flows observable, helps find and troubleshoot issues faster and deliver optimal performance. Its lightweight dashboard makes it easy to track key metrics of your Kafka clusters - Brokers, Topics, Partitions, Production, and Consumption.

Once-and-once-only delivery; Asynchronous messaging; Powerful protection; Simplified, smart management; Augmented security; Expanded client application options
Multi-Cluster Management — monitor and manage all your clusters in one place; Performance Monitoring with Metrics Dashboard — track key Kafka metrics with a lightweight dashboard; View Kafka Brokers — view topic and partition assignments, controller status; View Kafka Topics — view partition count, replication status, and custom configuration; View Consumer Groups — view per-partition parked offsets, combined and per-partition lag; Browse Messages — browse messages with JSON, plain text and Avro encoding; Dynamic Topic Configuration — create and configure new topics with dynamic configuration; Configurable Authentification — secure your installation with optional Github/Gitlab/Google OAuth 2.0
Statistics
GitHub Stars
-
GitHub Stars
11.5K
GitHub Forks
-
GitHub Forks
1.3K
Stacks
118
Stacks
16
Followers
187
Followers
19
Votes
11
Votes
0
Pros & Cons
Pros
  • 3
    Useful for big enteprises
  • 3
    Reliable for banking transactions
  • 2
    Secure
  • 1
    Broader connectivity - more protocols, APIs, Files etc
  • 1
    High Availability
Cons
  • 2
    Cost
No community feedback yet
Integrations
No integrations available
Docker
Docker
Java
Java
Kafka
Kafka
JSON
JSON

What are some alternatives to IBM MQ, Kafka UI?

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.

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.

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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