

Find out in this report how the two Message Queue (MQ) Software solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
It's a product which integrates the external systems with internal systems or among the systems themselves, making it an essential technology component required to integrate multiple systems.
It improved API latency from two seconds to 450 milliseconds for P99.
We reduced the database read load by around 30 to 40 percent and improved API response time by 20 to 30 percent, specifically for frequently accessed endpoints.
We cannot hold on to the project for a long time just to wait for IBM to fix the issues.
The response time for IBM MQ support could be better because when we are using IBM MQ and something goes wrong, support is required as the resource availability of the IBM product is very limited.
With containerized flavors of these products, we are having a tough time dealing with PMRs because the versions are new to IBM.
The documentation and community support for Redis are very strong, making troubleshooting quicker.
Since Redis is quite stable and well-documented, we have not needed much support, but when required, the response has been helpful.
IBM MQ handles many thousands of messages in a second, indicating good scalability.
In our environment, we do not have horizontal scaling for IBM MQ, but as demand increases, we would just vertically scale it.
We've got 12 VMs running, and it's very easy to scale.
Data migration and changes to application-side configurations are challenging due to the lack of automatic migration tools in a non-clustered legacy system.
I scale Redis horizontally using clustering and sharding, where data is distributed across multiple nodes to handle higher traffic and larger data sets.
With features such as clustering and replication, it can handle high traffic and a large database very effectively.
We have never had any downtime or crashes since it's been running.
The transaction is always guaranteed with IBM MQ, which is the main reason I have been working with it for fifteen years while dealing with financial transactions or messages.
Otherwise, they're completely stable.
Redis is fairly stable.
Having a graphical user interface would improve usability.
The pricing model for IBM MQ could be more flexible for clients.
They don't meet our standards due to the timing to get a person with knowledge.
Data persistence and recovery face issues with compatibility across major versions, making upgrades possible but downgrades not active.
Redis itself does not enforce consistency with the primary database, so developers need to carefully design cache invalidation strategies.
One issue is cache invalidation. Keeping cache data consistent with the source of truth can be tricky, especially in distributed systems.
It's not cheap.
It's possible to get some training, but the cost of this learning is expensive.
The price of IBM MQ is definitely on the higher side.
Since we use an open-source version of Redis, we do not experience any setup costs or licensing expenses.
The costs are primarily driven by memory consumption and cluster size, since Redis operates in-memory.
The pricing is reasonable for the performance provided.
These are financial transactions, so we do not want to lose the message at any cost.
There is a saying that for the last 30 years IBM MQ has never been hacked.
It's time-tested, very stable, highly resilient, and has all the features to troubleshoot even if something goes wrong.
It functions similarly to a foundational building block in a larger system, enabling native integration and high functionality in core data processes.
First is its in-memory preference, as Redis is extremely fast, making it ideal for caching and session management where low latency is critical.
Real API latency improved from around two seconds to approximately 450 milliseconds for P99.


| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 19 |
| Large Enterprise | 147 |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 6 |
| Large Enterprise | 10 |
IBM MQ provides reliable message delivery, supporting integration across systems with features like security and data integrity. It's widely used in financial and healthcare sectors, offering high scalability and availability while maintaining message consistency during downtime.
IBM MQ is known for its reliable and guaranteed message delivery, high scalability, and seamless integration with diverse systems. Users find its data integrity and robust security particularly beneficial, making it ideal for critical environments. It efficiently handles large message volumes, ensuring no data loss even during outages. Ease of use and initial setup, along with stability, are frequently noted advantages. However, users express a desire for better interfaces and enhanced cloud integration. Administration and security features are sometimes considered complex, necessitating streamlined processes and modern graphical interfaces. Expanded monitoring, competitive pricing, improved connectivity with platforms like Kafka and RabbitMQ, and seamless integration opportunities are commonly suggested areas for improvement.
What Are the Key Features of IBM MQ?IBM MQ is extensively implemented in critical industries such as finance and airlines, where reliable data exchange is essential. It supports message delivery in diverse platforms, facilitating crucial business transactions and scalable web services. Organizations in these sectors leverage its stability, high performance, and integration with both distributed and mainframe environments for consistent and reliable communication, helping to reduce the risk of data loss.
Redis offers high-speed, in-memory storage, renowned for real-time performance. It supports quick data retrieval and is used commonly in applications like analytics and gaming.
Renowned for real-time performance, Redis delivers high-speed in-memory storage, making it a favorite for applications needing quick data retrieval. Its diverse data structures and caching capabilities support a broad array of use cases, including analytics and gaming. Redis ensures robust scalability with master-slave replication and clustering, while its publish/subscribe pattern renders it reliable for event-driven applications. The solution integrates smoothly with existing systems, minimizing performance tuning needs. Although documentation on scalability and security could be improved, Redis remains cost-effective and stable, commonly utilized in cloud environments. Enhancing integration with cloud services like AWS and Google Cloud and refining GUI may improve usability.
What are the key features of Redis?Redis finds application across industries for tasks like caching to improve application performance and speed, minimizing database load. It enables real-time processing for session storage, push notifications, and analytics. As a messaging platform, Redis handles high traffic and supports replication and clustering for cross-platform scalability.
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