IBM MQ vs Apache Kafka: How Do They Differ?
Asynchronous communication between various CX applications has long been made possible by enterprise messaging solutions like IBM MQ and – more recently – Apache Kafka.
What is IBM MQ?
IBM MQ is a messaging middleware that integrates various business applications and data across multiple platforms faster and easier. It provides enterprise-grade messaging capabilities with a proven record for expertly and securely moving data.
Indeed, apps can communicate with the aid of IBM MQ. By transmitting message data via messaging queues, IBM MQ makes exchanging information easier for applications, services, systems, and files. This dramatically simplifies the process of developing and maintaining business applications.
Additionally, IBM MQ fits into several environments, such as on-premise, cloud, and hybrid cloud deployments, and is compatible with a broad range of computing systems. It also offers a global messaging backbone with a service-oriented architecture (SOA).
What is Apache Kafka?
Apache Kafka is an open-sourced, distributed streaming platform that enables the development of real-time, event-driven messaging and applications.
First created at the LinkedIn offices as a stream processing platform, Apache Kafka is now a notorious Scala-based decentralized data storage platform and open-source message broker.
As such, it allows developers to create applications that produce and consume various streams of data records.
Kafka allows users to swiftly transfer large amounts of streaming data between systems for data pipelines and in-the-moment analysis. Its messages are also kept on discs and replicated to prevent data loss.
IBM MQ vs Apache Kafka: Key Features
The following is a list of some of IBM MQ’s key attributes:
- A flexible messaging integration offers a single, reliable messaging backbone for diverse environments, from mainframe to mobile.
- Built-in security features to ensure that the data traveling between two applications is safe.
- Various operating modes, such as point-to-point, file transfer, publish/subscribe, and professional messaging features for reliably and efficiently transporting data.
- Scalability to add new applications – both online and offline – into a data flow.
The following is a list of some of Apache Kafka’s key attributes:
- The ability to handle large volumes of data streams with a guarantee of no downtime or data loss.
- High accuracy when handling data records, remaining fault tolerant.
- Integration simplicity through decoupling integration dependencies.
- Data gathering and location tracking features.
Systems can communicate asynchronously using IBM MQ and Apache Kafka, but they also include some unique characteristics that make them distinct from one another.
This article originally appeared on cxtoday.com. To read the full article, click here.
Nastel Technologies is the global leader in Integration Infrastructure Management (i2M). It helps companies achieve flawless delivery of digital services powered by integration infrastructure by delivering tools for Middleware Management, Monitoring, Tracking, and Analytics to detect anomalies, accelerate decisions, and enable customers to constantly innovate, to answer business-centric questions, and provide actionable guidance for decision-makers. It is particularly focused on IBM MQ, Apache Kafka, Solace, TIBCO EMS, ACE/IIB and also supports RabbitMQ, ActiveMQ, Blockchain, IOT, DataPower, MFT, IBM Cloud Pak for Integration and many more.
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