Kafka vs ActiveMQ – What’s the Difference? (Pros and Cons)
Kafka vs ActiveMQ – What’s the Difference? (Pros and Cons). Apache Kafka and ActiveMQ are among the widely used message brokers. First of all, they help organizations streamline their technical infrastructure and seamlessly connect applications. Secondly, by acting as an intermediary, they provide seamless data flow between programs without manual intervention or coding.
On one hand, Apache Kafka is a distributed streaming platform that handles large data streams in real time, while ActiveMQ provides out of the box features to make sharing information between client applications highly efficient. Both solutions easily handle mission critical workloads, so evaluating how each fits particular business needs is best.
This article Kafka vs ActiveMQ – What’s the Difference? discusses both tools in depth, including how they work, top features, pros and cons, and major differences. Read on!
What is Apache Kafka?
All in all, Apache Kafka is an open source distributed event streaming platform developed by the Apache Software Foundation. It provides a technical platform for streaming data between applications, websites and databases in near real time. The scalability, versatility and fault tolerance make it an ideal option for many large enterprises that process massive amounts of data.
This makes it highly popular among companies that require real time data insights for decision making.
How Apache Kafka Works
The brokers manage communications between clients and keep track of the current state of their topics. Producers publish data to topics while consumers subscribe to those topics to receive the published data. To ensure high availability and scalability, Apache Kafka provides a distributed commit log system to manage these messages across all its nodes. After that consumers act on the data almost immediately after it is produced.
Additionally, Kafka also supports stream processing with integrated connectors, which is used for source and sink operations on streaming data. Ideal platform for technical applications needing fast data streaming capabilities.
Features of Apache Kafka
Scalability
Primarily, designed to handle large amounts of data, allowing its users to scale up and out as demands increase. Basically, it handles scalability in four dimensions i.e event connectors, producers, processors, and consumers. Easily expanded across multiple nodes or machines, ensuring that it is able to handle extremely large volumes of incoming data. Moreover, it scales proportionally without causing any downtime.
Fault Tolerance
Fault tolerance feature ensures that messages are not lost even in the event of a node failure or network disruption in the message distribution system. Well, it handles failures with the master and databases efficiently such as such as aggregations and windowed joins. In turn, ideal for mission critical applications where you need high reliability.
Stream Processing
With Kafka’s integrated stream processing capabilities it enables users to quickly access real time insights from their data streams. This allows for advanced analytics and machine learning algorithms to be applied to streaming data in order to gain valuable insights.
Durability
Uses the distributed Commit Log to ensure messages persist on disk. This ensures that messages are retained and not lost, even if the system experiences a crash or network interruption.
Low Latency
Low latency messaging feature, Apache Kafka is able to provide extremely fast delivery of messages. So, making it ideal for applications requiring near real time performance. It also provides developers with a high throughput message delivery system with strong ordering guarantees.
Pros of Apache Kafka
- High performance mechanism that reduces server costs.
- Handles high volumes of data streams easily.
- Highly extensible as it integrates with many other applications
- Scales horizontally across many servers to maintain the order of data.
- Replicates data to ensure there is no loss in case of an IT disaster.
- Open source and free to use.
Cons of Apache Kafka
- Lacks a set of management and monitoring tools.
- Get’s slower when the number of queues in a cluster increases.
Up next with Kafka vs ActiveMQ – What’s the Difference? we introduce ActiveMQ.
What is ActiveMQ?
ActiveMQ is a high performance, open source messaging system developed by Apache Software Foundation. This message broker is designed to enhance messaging between applications. Basically, it acts as a message bridge that connects multiple components hosted in multiple servers or written in different languages.
Here, the ActiveMQ is written in the Java programming language. Provides communication between clients and servers in a way that integrates multiple transport protocols such as Java Message Service (JMS), WebSocket, STOMP, and OpenWire. Besides, it also supports multiple languages, including C++, Python, GO, and Ruby.
How ActiveMQ Works
Basically, ActiveMQ is designed to provide enterprise grade messaging solutions. These include high availability and clustering of different server instances. Others include message store operations like persistence/durable subscriptions/non-durable queues and point to point messaging. Furthermore, it includes native protocol implementations for MQTT over TCP/SSL for IoT applications and for AMQP with RabbitMQ clients for more advanced messaging scenarios.
Besides, ActiveMQ message broker facilitates reliable data exchange between clients and servers over a network. Uses clients and brokers to communicate, with the client responsible for sending messages and the broker responsible for forwarding those messages. The broker maintains an internal data structure to track which clients have subscribed to which topics or queues.
ActiveMQ also uses pluggable persistence mechanisms such as JDBC, KahaDB, or LevelDB for storage. Well, the ActiveMQ message broker additionally supports various communications protocols such as AMQP, MQTT, STOMP, etc. This provides technical users with messaging flexibility in how they exchange messages.
Features of ActiveMQ
Multiple Connectivity Options
Supports multiple connectivity options such as XMPP, UDP, STOMP, HTTP/S, and SSL. This provides multiple options for connectivity. Besides, it allows various systems to use their preferred choice of protocols for communication.
JMS Compliant
Designed to comply with the JMS 1.1 standards. In essence, JMS spec provides a standard mechanism for both synchronous and asynchronous message delivery, durability, and single message delivery.
Multi Platform
Provides client APIs for all popular programming languages, including Python, PHP, Perl, .NET, C, C++, Java, Ruby, etc. Runs in JVM, although you write clients in any supported language.
Pluggable Architecture
Moreover, ActiveMQ allows users to customize various options, such as security. Basically, you customize authorization and authentication processes depending on application needs.
Security
Provides various security features such as authentication, authorization, SSL encryption, etc. These security features ensure there is secure and reliable communication between clients and servers. All in all, gives you the complete control over who can access the message broker and what operations are performed on it.
Pros of ActiveMQ
- Open source message broker that’s free to use.
- Designed with high performance to process millions of messages per second, especially for high throughput messaging applications.
- Flexible architecture that enables users to deploy it in a variety of architectures, including master/slave and peer to peer.
- Easily scales up or down to process dynamic workloads.
Cons of ActiveMQ
- Limited documentation that new users find hard to understand.
- Vulnerable to security attacks if not configured properly.
- Does not provide comprehensive monitoring tools, which makes it difficult to track activities in the message broker.
Main Differences Between Kafka and ActiveMQ
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Supported Languages
Apache Kafka supports multiple programming languages such as PHP, Ruby, Node.js, Python, and Go. On the other hand, ActiveMQ supports C, C++, Java, Perl, PHP, and Python.
Main Functionality
Both, Kafka and ActiveMQ are application messaging systems. However, Kafka is more of an event streaming platform since it analyzes continuous data streams. ActiveMQ is a message broker that enables seamless data exchange between applications and services. In essence, it provides a standardized flow of data between interdependent services.
Event streaming manages and stores data related to events together rather than an event at a time. The data is processed and stored, allowing consumers to replay events. On the other hand, message brokers delete data after receiving it.
Use Cases
Both, Kafka and ActiveMQ have a wide variety of use cases. Kafka is ideal for organizations that require reliable and organized storage at scale. It processes large amounts of data, making it suitable for high volume workloads. You can use Kafka for real time processing needs, such as monitoring IoT hardware. Also useful when tracking website traffic. Finally, you use Kafka for data aggregation and centralization i.e operational metrics, KPIs, and log aggregation.
Oppositely, ActiveMQ is ideal for exchanging data in multi application architecture. Enables users to set up highly complex message routing. As a result, you use ActiveMQ for high performance data streaming and asynchronous messaging. You can also use it for transactional messaging, such as financial deposits and withdrawals.
Throughput
Apache Kafka is a distributed system. This ensures it can handle massive amounts of data with high performance. Besides, it replicates partitions and scales easily to provide high availability. ActiveMQ maintains a delivery state for each message, which results in low throughput. However, the processing is time consuming. In essence, ActiveMQ is fast when processing small amounts of data.
Message and Data Storage
Data in both Apache Kafka and ActiveMQ is handled differently. Kafka transfers and stores events/messages permanently. It’s possible to set retention times depending on the use case, which can be as low as a millisecond. As a result, it helps in eliminating unnecessary data retention. Besides, Kafka either preserves or ignores messaging orders depending on the partition method used.
On the other hand, ActiveMQ leverages the JMS API selector to manage messages. The push mechanism enables providers to push messages to consumers. Besides, ActiveMQ filters messages such that consumers only receive the messages they want. Once a message is delivered, ActiveMQ provides a message acknowledgement. ActiveMQ does not provide message persistence. It retains messages temporarily in virtual memory before being deleting them.
Message Protocols
Message protocols provide interoperability between brokers and clients. This enables clients to move across different brokers without any code changes. Kafka has its own wire protocol implemented using Node, .NET, Python, and Java. On the other hand, ActiveMQ is multiprotocol. It supports multiple protocols, including STOMP, MQTT, OpenWire, and AMQP.
That is it. Let’s conclude Kafka vs ActiveMQ – What’s the Difference?
Kafka vs ActiveMQ - What's the Difference? Conclusion
Summing up, Apache Kafka and ActiveMQ are powerful messaging systems with unique features and benefits. On one hand, Apache Kafka provides a reliable message delivery system for applications that require lightning-fast stream processing abilities. On the other hand, ActiveMQ is ideal if your workload demands high throughput and multiple communication protocols. You should always choose the right platform to use based on workload requirements.
Have a look at our Kafka content in the blog over here.
