Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics.
The Apache community provides support for the open-source version.
There is plenty of community support available online.
With containerized flavors of these products, we are having a tough time dealing with PMRs because the versions are new to IBM.
I would rate technical support as an eight.
Customers have not faced issues with user growth or data streaming needs.
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.
Apache Kafka is stable.
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.
The performance angle is critical, and while it works in milliseconds, the goal is to move towards microseconds.
A more user-friendly interface and better management consoles with improved documentation could be beneficial.
We are always trying to find the best configs, which is a challenge.
Having a graphical user interface would improve usability.
We are dealing with IBM MQ client applications mostly.
The open-source version of Apache Kafka results in minimal costs, mainly linked to accessing documentation and limited support.
Its pricing is reasonable.
I am not exactly sure about the licensing cost compared to similar products, but I assume it is affordable since we continue to use it, and it is also used by our customers.
IBM MQ is pretty reasonable when compared to IBM ESB.
Apache Kafka is effective when dealing with large volumes of data flowing at high speeds, requiring real-time processing.
It allows the use of data in motion, allowing data to propagate from one source to another while it is in motion.
These are financial transactions, so we do not want to lose the message at any cost.
IBM MQ processes many thousands of messages in a second, which is efficient for handling high transaction volumes.
Apache Kafka is an open-source distributed streaming platform that serves as a central hub for handling real-time data streams. It allows efficient publishing, subscribing, and processing of data from various sources like applications, servers, and sensors.
Kafka's core benefits include high scalability for big data pipelines, fault tolerance ensuring continuous operation despite node failures, low latency for real-time applications, and decoupling of data producers from consumers.
Key features include topics for organizing data streams, producers for publishing data, consumers for subscribing to data, brokers for managing clusters, and connectors for easy integration with various data sources.
Large organizations use Kafka for real-time analytics, log aggregation, fraud detection, IoT data processing, and facilitating communication between microservices.
IBM MQ is a middleware product used to send or exchange messages across multiple platforms, including applications, systems, files, and services via MQs (messaging queues). This solution helps simplify the creation of business applications, and also makes them easier to maintain. IBM MQ is security-rich, has high performance, and provides a universal messaging backbone with robust connectivity. In addition, it also integrates easily with existing IT assets by using an SOA (service oriented architecture).
IBM MQ can be deployed:
IBM MQ supports the following APIs:
IBM MQ Features
Some of the most powerful IBM MQ features include:
IBM MQ Benefits
Some of the benefits of using IBM MQ include:
Reviews from Real Users
Below are some reviews and helpful feedback written by IBM MQ users who are currently using the solution.
PeerSpot user Sunil S., a manager at a financial services firm, explains that they never lose messages are never lost in transit, mentioning that he can store messages and forward them as required: "Whenever payments are happening, such as incoming payments to the bank, we need to notify the customer. With MQ we can actually do that asynchronously. We don't want to notify the customer for each and every payment but, rather, more like once a day. That kind of thing can be enabled with the help of MQ."
Another PeerSpot reviewer, Luis L. who is a solutions director at Thesys Technologies, says that IBM MQ is a valuable solution and is "A stable and reliable software that offers good integration between different systems."
The head of operations at a financial services firm notes that "I have found the solution to be very robust. It has a strong reputation, is easy to use, simple to configure in our enterprise software, and supports all the protocols that we use."
In addition, a Software Engineer at a financial services firm praises the security benefits of it and states that “it has the most security features I've seen in a communication solution. Security is the most important thing for our purposes."
PubSub+ Platform supports real-time shipment tracking, IT event management in multiclouds, and connects legacy and cloud-native systems for application modernization. It's utilized for trading, streaming market data, and app-to-app messaging, enhancing event-driven architectures with reliable message queuing.
Organizations adopt PubSub+ to efficiently transport events across hybrid and cloud environments, managing audit trails and long processing tasks. The platform aids integration through dynamic data publication, event mesh capabilities, and WAN optimization. Features like seamless integration, protocol agnosticism, and flexible topic hierarchy enhance versatility. Solace Admin Utility simplifies configuration and management, while the event portal allows hybrid deployment.
What are the key features of PubSub+ Platform?PubSub+ is implemented in industries requiring real-time data handling and integration between disparate systems. Financial institutions use it for trading and streaming market data, while logistics companies benefit from real-time shipment tracking. Enterprises apply it to modernize operations by connecting legacy systems with cloud-native applications, enhancing their architecture and ensuring data reliability across environments.
