Top 10 HiveMQ Alternatives & Competitors

Top 10 Alternatives to HiveMQ Recently Reviewed By G2 Community

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EMQX
By EMQ
4.6/5
(23)
Product Description
EMQ is an innovative open-source software provider with strong roots in IoT data infrastructure, delivering the world’s leading cloud-native MQTT messaging, streaming database, and edge computing solutions. Since 2017 EMQ has been developing a high-performance and massively scalable distributed MQTT messaging server¬ – EMQX to accelerate the connectivity and integration of a wide spectrum of IoT applications and data across multiple platforms. So far, EMQX has been adopted by more than 10,000 enterprise users from over 50 countries, connecting more than 100 million IoT devices worldwide. EMQ’s robust and flexible edge-to-cloud IoT data solutions encompass a suite of technologies designed for IoT applications: reliability, security, availability, scalability, latency & throughput. This enables successful enterprise-grade IoT deployments with ease and scale.
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Reviewers say compared to HiveMQ, EMQX is:
More usable
Categories in common with HiveMQ:
Message Queue (MQ)
IoT Connectivity Management
Industrial IoT

MuleSoft Anypoint Platform
By Salesforce
4.5/5
(733)
Product Description
Anypoint Platform™ is a complete platform that lets companies realize business transformation through API-led connectivity. It is is a unified, flexible integration platform that solves the most challenging connectivity problems across SOA, SaaS and APIs.
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Reviewers say compared to HiveMQ, MuleSoft Anypoint Platform is:
Slower to reach roi
Categories in common with HiveMQ:
Message Queue (MQ)

SAP Integration Suite
By SAP
4.3/5
(324)
Product Description
SAP Integration Suite powers applications that deliver real-time insights to drive more effective and timely decision making. Dramatically accelerate analytics, business processes, sentiment data processing, and predictive capabilities to run your business in real-time.
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Reviewers say compared to HiveMQ, SAP Integration Suite is:
Slower to reach roi
More expensive
Categories in common with HiveMQ:
Message Queue (MQ)

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RabbitMQ
By Broadcom
4.1/5
(47)
Product Description
Messaging that just works
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Reviewers say compared to HiveMQ, RabbitMQ is:
Slower to reach roi
Categories in common with HiveMQ:
Message Queue (MQ)

Particle
By Particle
4.5/5
(195)
Product Description
Particle offers a suite of hardware and software tools to help you prototype, scale, and manage your Internet of Things products.
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Reviewers say compared to HiveMQ, Particle is:
Slower to reach roi
Categories in common with HiveMQ:
Industrial IoT

IBM MQ
By IBM
4.3/5
(174)
Product Description
IBM® MQ, formerly WebSphere MQ, is messaging middleware that simplifies and accelerates the integration of diverse applications and data across multiple platforms. It uses message queues to exchange information and offers a single messaging solution for cloud, on premise, mobile and IoT environments. By connecting virtually everything, from a simple pair of applications to the most complex business environments, it improves responsiveness, controls costs, reduces risk and provides real-time insight from data. It is available in a standard edition, an advanced edition, as an appliance and in a z/OS version.
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Reviewers say compared to HiveMQ, IBM MQ is:
Slower to reach roi
Categories in common with HiveMQ:
Message Queue (MQ)

Geotab
By Geotab
4.5/5
(178)
Product Description
Geotab is a global leader in telematics, providing open platform fleet management solutions to businesses of all sizes. Geotab's intuitive, full-featured solutions help businesses better manage their drivers and vehicles by extracting accurate and actionable intelligence from real-time and historical trips data.
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Reviewers say compared to HiveMQ, Geotab is:
Slower to reach roi
Categories in common with HiveMQ:
Industrial IoT

Apache ActiveMQ
By The Apache Software Foundation
4.3/5
(16)
Product Description
Apache ActiveMQ is a popular and powerful open source messaging and Integration Patterns server.
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Categories in common with HiveMQ:
Message Queue (MQ)

Apache Kafka
By The Apache Software Foundation
4.5/5
(131)
Product Description
Apache Kafka is an open-source distributed event streaming platform developed by the Apache Software Foundation. It is designed to handle real-time data feeds with high throughput and low latency, making it ideal for building data pipelines, streaming analytics, and integrating data across various systems. Kafka enables organizations to publish, store, and process streams of records in a fault-tolerant and scalable manner, supporting mission-critical applications across diverse industries. Key Features and Functionality: - High Throughput and Low Latency: Kafka delivers messages at network-limited throughput with latencies as low as 2 milliseconds, ensuring efficient data processing. - Scalability: It can scale production clusters up to thousands of brokers, handling trillions of messages per day and petabytes of data, while elastically expanding and contracting storage and processing capabilities. - Durable Storage: Kafka stores streams of data safely in a distributed, durable, and fault-tolerant cluster, ensuring data integrity and availability. - High Availability: The platform supports efficient stretching of clusters over availability zones and connects separate clusters across geographic regions, enhancing resilience. - Stream Processing: Kafka provides built-in stream processing capabilities through the Kafka Streams API, allowing for operations like joins, aggregations, filters, and transformations with event-time processing and exactly-once semantics. - Connectivity: With Kafka Connect, it integrates seamlessly with hundreds of event sources and sinks, including databases, messaging systems, and cloud storage services. Primary Value and Solutions Provided: Apache Kafka addresses the challenges of managing real-time data streams by offering a unified platform that combines messaging, storage, and stream processing. It enables organizations to: - Build Real-Time Data Pipelines: Facilitate the continuous flow of data between systems, ensuring timely and reliable data delivery. - Implement Streaming Analytics: Analyze and process data streams in real-time, allowing for immediate insights and actions. - Ensure Data Integration: Seamlessly connect various data sources and sinks, promoting a cohesive data ecosystem. - Support Mission-Critical Applications: Provide a robust and fault-tolerant infrastructure capable of handling high-volume and high-velocity data, essential for critical business operations. By leveraging Kafka's capabilities, organizations can modernize their data architectures, enhance operational efficiency, and drive innovation through real-time data processing and analytics.
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Categories in common with HiveMQ:
Message Queue (MQ)