Apache Kafka is an open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java. The Kafka event streaming platform is used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.
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IBM MQ
Score 9.0 out of 10
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IBM MQ (formerly WebSphere MQ and MQSeries) is messaging middleware.
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Agentforce Commerce
Score 8.1 out of 10
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Salesforce Agentforce Commerce (formerly Commerce Cloud, and Demandware before that) is a cloud-based eCommerce solution for enterprises with merchandising tools, such as sorting, filtering, and image zooming, allowing customers to browse products.
$4
per month
Pricing
Apache Kafka
IBM MQ
Salesforce Agentforce Commerce
Editions & Modules
No answers on this topic
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Offerings
Pricing Offerings
Apache Kafka
IBM MQ
Agentforce Commerce
Free Trial
No
Yes
No
Free/Freemium Version
No
Yes
No
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
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B2B Commerce:
Starter - $4 price/order
Growth - $6 price/order
Plus - $8 price/order
B2C Commerce:
Starter - 1% Gross Merchandise Value
Growth - 2% Gross Merchandise Value
Plus - 3% Gross Merchandise Value
B2B2C Commerce:
1% Gross Merchandise Value
More Pricing Information
Community Pulse
Apache Kafka
IBM MQ
Salesforce Agentforce Commerce
Considered Multiple Products
Apache Kafka
Verified User
Analyst
Chose Apache Kafka
Confluent Cloud is still based on Apache Kafka but it has a subscription fee so, from a long term perspective, it is wiser to deploy your own Kafka instance that spans public and private cloud. Amazon Kinesis, Google Cloud Pub/Sub do not do well for a very number of messages …
Kafka is faster and more scalable, also "free" as opensource (albeit we deploy using a commercial distribution). Infrastructure tends to be cheaper. On the other hand, projects must adapt to Kafka APIs that sometimes change and BAU increases until a major 1.x version comes out …
Apache Kafka may be a better option in comparison with IBM MQ its real-time data streaming and large data payload service. It depends upon the specific requirement and meets those needs. MuleSoft any point platform is very easy to connect to various other types of platforms in …
I've also used Apache Kafka and RabbitMQ. Compared to these, IBM MQ offers superior reliability and transactional integrity, making it a better choice for complex, mission-critical enterprise environments where message delivery and security are paramount. We chose IBM MQ for …
Kafka is renowned for its impressive throughput, fault tolerance, and real-time data streaming capabilities. Nonetheless, IBM MQ remains the preferred choice due to its unwavering commitment to guaranteed delivery and exceptional reliability. Fault-Tolerant Architectures of IBM …
Both are useful in their own right and we actually use IBM MQ together with PCWP. IBM MQ automates our tasks and saves a lot of tedious work we would otherwise have to do manually.
We found IBM MQ very easy to get started and quick to learn by the new users with a short learning curve and seamlessly integrates with IBM products, and quick to perform self-service analytics and make informed business decisions. IBM MQ is also very straightforward in …
IBM MQ is very stable and a proven product compared to other Messaging platforms available. Performance was better than WSO2 product and also the RabbitMQ. Though Kafka and IBM MQ is not directly comparable, Kafka is more suited for event based systems and also where there is …
Apache Kafka is well-suited for most data-streaming use cases. Amazon Kinesis and Azure EventHubs, unless you have a specific use case where using those cloud PaAS for your data lakes, once set up well, Apache Kafka will take care of everything else in the background. Azure EventHubs, is good for cross-cloud use cases, and Amazon Kinesis - I have no real-world experience. But I believe it is the same.
In the context of Internet of Things (IoT) applications, IBM MQ plays a pivotal role in managing the substantial data streams emanating from interconnected devices. Its primary function is to guarantee the dependable transmission and processing of data, catering to a diverse range of IoT use cases, including but not limited to smart city initiatives, healthcare monitoring systems, and industrial automation solutions. In the telecommunications sector, IBM MQ is employed for message routing, call detail record (CDR) processing, and network management to ensure real-time data exchange and fault tolerance. When managing the supply chain and logistics, IBM MQ is used to ensure timely and accurate communication between different entities, including suppliers, warehouses, and transportation providers. IBM MQ can be cost-prohibitive for smaller organizations due to licensing and maintenance costs. In such cases, open-source or lightweight messaging solutions may be more appropriate. For scenarios requiring extremely low-latency, real-time data exchange, and high throughput, other messaging technologies, like Apache Kafka, may be more suitable due to their specialized design for such use cases.
Global Sites; larger commerce organizations but not too large where the % rev-share would affect its feasibility in a feature comparison. Salesforce is rock solid in infrastructure and rarely has outages or issues; it scaled appropriately for holiday peak and was able to accomplish anything we put our minds to as long as we staffed development appropriately. The latter, however, is not to be overlooked. Developers are necessary and expensive.
Really easy to configure. I've used other message brokers such as RabbitMQ and compared to them, Kafka's configurations are very easy to understand and tweak.
Very scalable: easily configured to run on multiple nodes allowing for ease of parallelism (assuming your queues/topics don't have to be consumed in the exact same order the messages were delivered)
Not exactly a feature, but I trust Kafka will be around for at least another decade because active development has continued to be strong and there's a lot of financial backing from Confluent and LinkedIn, and probably many other companies who are using it (which, anecdotally, is many).
The documentation is very clear,It is understandable and the support helps to configure it in the best way.
Server guidelines make it possible to get the most out of work management. It's broad, we can work with different operating systems, I really recommend using linux.
It is highly compatible with systems, brockers, applications, and data accumulation programs, it is possible to configure everything so that after the installation of programs, they can communicate with each other and then throw data to an external program that accumulates it and represents in clear details of steps to follow and make business decisions.
Traffic - When we have sales, our traffic will increase exponentially and their cloud can handle the huge uptick in traffic we receive without overloading our servers.
Site updates - it continually monitors in the background for any upgrades or updates needed so we don't have to go in and do it ourselves. A real time saver!
Integration - outside plugins and add-ons are easy to install with Salesforce commerce cloud as it allows a seamless integration of extra plug ins onto our site.
Sometimes it becomes difficult to monitor our Kafka deployments. We've been able to overcome it largely using AWS MSK, a managed service for Apache Kafka, but a separate monitoring dashboard would have been great.
Simplify the process for local deployment of Kafka and provide a user interface to get visibility into the different topics and the messages being processed.
Learning curve around creation of broker and topics could be simplified
There is limitation on number of svrconn connections you can have to MQ on the mainframe which has been an major issue for us. This has been an issue for us for over 4 years and still no fix although I am aware IBM have been working on a solution over the last year.
When upgrading to MQ V9.3 on our MQ appliances there is no fall-back option. This was the same for MQ V9.2 upgrade from MQ V9.0. For production upgrades this I believe is not acceptable.
AMS is not supplied as part of the standard mainframe MQ licence. You need an extra licence. IBM tell customers how important security and protecting data is yet they still want to charge for this software. The cost of MQ on the mainframe is not cheap so I would expect AMS to be part of the base product.
The UX within the Business Manager portion of Demandware, the primary interface for marketers, is generally a confusing, inconsistent mess. Particularly infuriating are the lack of consistency for search and sort behavior within the tool.
A number of useful features, such as the ability to set schedules or tie features to unique customer segments, have seemingly arbitrary limitations imposed.
Demandware's idea of leveraging the community to be a learning resource and a sounding board for new ideas and features is a nice theory, but in practice it doesn't work for businesses with a lot of customization. I'm left with the impression that individual support is not a priority.
A huge factor influencing our decision to remain on the Demandware platform is that our new parent company is standardizing all its luxury brands in the US on it. We are fortunate. However, even if we had remained an independent company, I believe we would continue on the Demandware platform for all the reasons outlined in this review. I appreciate the stability the platform has provided to our eCommerce site in the last three years as well as the continuous improvements and technological advances being rolled out that will allow us to keep the site fresh, engaging, modern and stable. I've heard many horror stories from colleagues on other platforms who struggle with the expense and complexity involved with making what should be minor and simple changes and updates to their sites.
Apache Kafka is highly recommended to develop loosely coupled, real-time processing applications. Also, Apache Kafka provides property based configuration. Producer, Consumer and broker contain their own separate property file
I give it a nine because it has significantly improved my team's data reliability and operational efficiency. Its great security features give us peace of mind, knowing our sensitive data is well protected. While the setup might initially be complex, I believe the long-term benefits far outweigh this hurdle.
The overall ease of using the system. Consolidation in location for our team members. Mobile application for on the go research, as many of our team members are constantly traveling to job sites or to meet clients. No more duplicate calls to current customers, since we have 12 different divisions that span the company. Mostly the ability to look at the database when our team members begin cultivating a new lead/prospect with a potential customer to see if anyone within the team has a relationship with that person or the company they work for.
The messages are delivered instantly with this software and it integrates with our technology stack, in terms of availability we only had one failure when we were doing some testing and integration with third parties, the features of this software make it always available and its deployment is easy for the company, it does not generate expenses due to failures
Support for Apache Kafka (if willing to pay) is available from Confluent that includes the same time that created Kafka at Linkedin so they know this software in and out. Moreover, Apache Kafka is well known and best practices documents and deployment scenarios are easily available for download. For example, from eBay, Linkedin, Uber, and NYTimes.
There are very specific things that must be elevated to more specialized areas of support, but the common support is very agile when receiving questions or when we leave concerns in real time. I recommend the support of the program in this regard.
They are very responsive and a support technician will be assigned quickly. Even if there is further clarification needed for the ticket, or a solution is not immediately available, you feel that someone is there and staying on top of the issue. Most common issues are resolved quickly and satisfactorily.
I used other messaging/queue solutions that are a lot more basic than Confluent Kafka, as well as another solution that is no longer in the market called Xively, which was bought and "buried" by Google. In comparison, these solutions offer way fewer functionalities and respond to other needs.
We found IBM MQ very easy to get started and quick to learn by the new users with a short learning curve and seamlessly integrates with IBM products, and quick to perform self-service analytics and make informed business decisions. IBM MQ is also very straightforward in creating simple and best reports, which are very profitable and productive.
When I think of Salesforce products, I sometimes think of them interchangeably as one big lump. It's hard not to be incredibly immersed in the ecosystem day in and day out and taking advantage of resources like Trailhead. While Microsoft Dynamics compares in quality and offerings, it doesn't offer the same engagement and resources as Salesforce in its communications, social, and marketing, which makes a difference in terms of relevance and help. Commerce Cloud comes with the support you need to succeed and the tools you need to grow. In a high demand consumer world, we need products like this to keep up and get ahead. The minute we catch up, we're behind. Salesforce helps you stay on pace and create the unique and personalized experiences customers everywhere expect.
Positive: Get a quick and reliable pub/sub model implemented - data across components flows easily.
Positive: it's scalable so we can develop small and scale for real-world scenarios
Negative: it's easy to get into a confusing situation if you are not experienced yet or something strange has happened (rare, but it does). Troubleshooting such situations can take time and effort.