What is Message Queue Software?

Message queue software is an asynchronous communication middleware that connects applications. Traditional monolithic software is built to communicate with itself or a few other applications. When the software sends or receives data from another software, this data is called a message. It is difficult to send and receive data to another app due to different operating systems, network protocols, and programming languages. Message queue software solves these problems by handling messages for applications from different environments. It creates a new high availability, high reliability, high throughput, and low latency environment to send and receive messages from one application to another. As the name suggests, MQ software lines up different messages by “queue” and processes each message through standardized methods. This helps companies to develop high-performance cloud services and apps such as microservices that can communicate with other applications and operating systems without worrying about compatibility issues. In the early years, big companies invested heavily in proprietary software and middleware that could connect their products with each other. Using the same IT stacks and standards, these companies can create connected applications. With the vast network of applications connected by middleware, users can solve various complex problems that require multiple inputs and outputs from different environments. However, only big companies with big budgets can afford to develop this approach. For most companies and non-business users who use different network standards, programming languages, and data structures, connected applications seem to be unobtainable. This is why there are many business issues that seem to be easy to solve but are technically challenging to implement. For example, hospitals and insurance companies can’t share patient data automatically because their applications aren’t compatible in communicating with each other. Those who managed to set up the connectivity may still use proprietary protocols such as raw UDP, TCP, and HTTP, which are hard to scale and integrate with other applications. To solve this issue, early open-source organizations build open source message brokers specific to a language environment like Java and Python. Later big companies began building their own messaging system for others, such as AWS and IBM MQ, to create enterprise messaging platforms that run on their own IT systems. Software buyers can select the best message queue web services or on-premises software to connect various assets such as big data servers to the internet of things (IoT). What Does MQ Stand For? MQ stands for Message Queue. A “message” is data that transfers from one party to another. A “queue” is how that message is transferred and processed from one party to another.

What are the Common Features of Message Queue Software?

The following are some core features within Message Queue Software that can help users ensure high availability of message queuing services: Message query: MQ allows applications to query messages by ID, topics, keys, and contents. This enables the user to organize messages based on custom rules. Message tracing: MQ can trace routing information from the producer of the message to the consumer. This allows users to analyze metadata on the message producer and consumer for network performance issues. Dead-letter queue: MQ supports dead-letter queues (DLQ) to save messages that can’t be processed for debugging to determine why the queueing process failed. Message blocklist and allowlist: MQ supports account-based blocklist and allowlist policies to authorize or unauthorize messages from internal and external parties. Multiple message processes: Message queue processes can be created for different models. In a peer-to-peer model, a producer sends one message to one consumer. In a pub/sub model, producers can send group messages to consumers with the same cluster ID. In RPC (request/reply) model, MQ can load balance messages back and forth between producer and consumer. Dashboard: A user-friendly dashboard can visualize comprehensive and multidimensional metrics of message product and consumption based on clusters, topics, instances, and groups. This will spot trends for server resource allocation and security improvement. Monitoring and alerting: Messaging activities can be monitored in real time, and alerts can be sent to notify the IT and data team to resolve issues in a timely manner.

What are the Benefits of Message Queue Software?

Decoupling: Message queue tools decouple (separate) applications and message services. This simplifies CI/CD development so developers can design and update core components without worrying about the message components. Load shifting: Messages can automatically be queued according to their size, frequency, and quantity. When there is a large number of message requests, servers can fail to process this amount of volume. It will either crash or indiscriminately reject all incoming messages. Without load shifting, message disruption will halt online business operations and negatively affect revenue. Scalability: MQ servers can be integrated with other applications and be allocated an appropriate amount of resources based on needs. This saves users time from manually changing the message process during disruptions or software upgrades.

Page 2 | Best Message Queue (MQ) Software: User Reviews from October 2026

Lobster Data Platform

Lobster is a data integration platform for complex, multi-party supply chains. It connects suppliers, partners and systems across EDI, APIs, legacy databases and cloud apps in one place, with 90+ pre-built connectors, 2000+ customers and 20 years of supply chain expertise behind it. Lobster gives teams control over how data flows across their supply chain, so they can build, customise and maintain integrations themselves. Teams can also see, enrich and act on data as it moves across systems and partners, using workflows, exception handling and human input where needed. Purpose-built for logistics, manufacturing and retail, Lobster helps organisations reduce integration complexity, respond faster when requirements change, and keep their supply chain data flowing as operations evolve.

Average Rating: 4.6/5.0

Total Reviews: 106

How Do G2 Users Rate Lobster Data Platform?

Application Integration: 9.8/10 (Category avg: 8.7/10)
Plugins and integrations: 8.3/10 (Category avg: 8.4/10)
Data Integration: 9.4/10 (Category avg: 8.8/10)
Has the product been a good partner in doing business?: 8.9/10 (Category avg: 8.7/10)

Who Is the Company Behind Lobster Data Platform?

Seller: Lobster Data GmbH
Company Website:
Year Founded: 2002
HQ Location: Tutzing, Germany
LinkedIn® Page: www.linkedin.com
333 employees on LinkedIn®

Who Uses This Product?

Top Industries: Logistics and Supply Chain, Transportation/Trucking/Railroad
Company Size: 61% Medium, 26% Large

What Do G2 Reviewers Say About Lobster Data Platform?

AI-generated summary from verified user reviews

Pros

Users appreciate the ease of use of Lobster Data Platform, highlighting its quick setup and reliable performance.
Users praise the excellent customer support of Lobster Data Platform for its quick assistance and effective onboarding.
Users appreciate the seamless integration capabilities of Lobster Data Platform, effectively connecting various internal and external systems.
Users value the seamless integrations of Lobster Data Platform, enabling efficient connectivity across internal and external systems.
Users love the intuitive user interface of Lobster Data Platform, enabling quick project realization and satisfaction.

Cons

Users find the complexity of Lobster Data Platform overwhelming due to its numerous functions and options.
Users express concerns over the inconsistent documentation and interface changes that hinder usability and clarity in Lobster Data Platform.
Users find the missing features in Lobster Data Platform limiting, particularly with API management and documentation.
Users face poor documentation that lacks harmony and clarity, leading to confusion and unexpected issues during use.
Users find the complex usability challenging, especially with many functions and intricate process chains.

What Are Recent G2 Reviews of Lobster Data Platform?

"Intuitive Platform, very easy to use, Needs Faster Bug Fixes"

Rating: 4.5/5.0 stars

— Felix B.

Best Message Queue Systems - Page 2

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Category Stats (Oct 2026)

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