{"id":14609,"date":"2018-04-25T10:17:11","date_gmt":"2018-04-25T10:17:11","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=14609"},"modified":"2018-04-25T10:17:11","modified_gmt":"2018-04-25T10:17:11","slug":"advantages-and-disadvantages-of-kafka","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/advantages-and-disadvantages-of-kafka\/","title":{"rendered":"Advantages and Disadvantages of Kafka"},"content":{"rendered":"

In our last Kafka Tutorial, we discussed Books for Kafka<\/strong>. Today, we will discuss the Advantages and Disadvantages of Kafka<\/strong>. Because, it is very important to know the limitations of any technology before using it, same in case of advantages. <\/span><\/p>\n

So, let’s discuss Kafka Advantage and Disadvantage in detail.<\/span><\/p>\n

Advantages of Kafka<\/span><\/h2>\n

So, here we are listing out some of the advantages of Kafka. Basically, these Kafka advantages are making Kafka ideal for our data lake implementation. So, let’s start learning advantages of Kafka in detail:<\/p>\n

\"Advantages<\/a>

Kafka Pros and Cons – Kafka Advantages<\/p><\/div>\n

a.\u00a0High-throughput<\/strong>
\nWithout having not so large hardware, Kafka is capable of handling high-velocity and high-volume data. Also, able to support message throughput of thousands of messages per second. <\/span><\/p>\n

b.\u00a0Low Latency<\/strong>
\nIt is capable of handling these messages with the very low latency of the range of milliseconds, demanded by most of the new use cases. <\/span><\/p>\n

c.\u00a0Fault-Tolerant<\/strong>
\nOne of the best advantages is Fault Tolerance. There is an inherent capability in Kafka, to be resistant to node\/machine failure within a cluster. <\/span><\/p>\n

d.\u00a0Durability<\/strong>
\nHere, durability refers to the persistence of data\/messages on disk. Also, messages replication is one of the reasons behind durability, hence messages are never lost.<\/span><\/p>\n

e.\u00a0<\/strong><\/span>Scalability<\/strong>
\nWithout incurring any downtime on the fly by adding additional nodes, Kafka can be scaled-out. Moreover, inside the Kafka cluster, the message handling is fully transparent and these are seamless. <\/span><\/p>\n

f.\u00a0Distributed<\/strong>
\nThe distributed architecture of Kafka makes it scalable using capabilities like replication and partitioning. <\/span><\/p>\n

g.\u00a0Message Broker Capabilities<\/strong>
\nKafka tends to work very well as a replacement for a more traditional message broker. Here, a message broker refers to an intermediary program, which translates messages from the formal messaging protocol of the publisher to the formal messaging protocol of the receiver. <\/span><\/p>\n

h.\u00a0High Concurrency<\/strong>
\nKafka is able to handle thousands of messages per second and that too in low latency conditions with high throughput. In addition, it permits the reading and writing of messages into it at high concurrency.<\/span><\/p>\n

i.\u00a0By Default Persistent<\/strong>
\nAs we discussed above that the messages are persistent, that makes it durable and reliable. <\/span><\/p>\n

j.\u00a0Consumer Friendly<\/strong>
\nIt is possible to integrate with the variety of consumers using Kafka. The best part of Kafka is, it can behave or act differently according to the consumer, that it integrates with because each customer has a different ability to handle these messages, coming out of Kafka. Moreover, Kafka can integrate well with a variety of consumers written in a variety of languages. <\/span><\/p>\n

k.\u00a0Batch Handling Capable (ETL like functionality)<\/strong>
\nKafka could also be employed for batch-like use cases and can also do the work of a traditional ETL, due to its capability of persists messages.<\/span><\/p>\n

l. Variety of Use Cases<\/strong>
\nIt is able to manage the variety of use cases commonly required for a Data Lake. For Example log aggregation, web activity tracking, and so on. <\/span><\/p>\n

m.\u00a0Real-Time Handling<\/strong>
\nKafka can handle real-time data pipeline. Since we need to find a technology piece to handle real-time messages from applications, it is one of the core reasons for Kafka as our choice.<\/span><\/p>\n

Disadvantages of Kafka<\/span><\/h2>\n
\"Advantages<\/a>

Cons of Kafka – Apache Kafka Disadvantages<\/p><\/div>\n

It is good to know Kafka\u2019s limitations even if its advantages appear more prominent then its disadvantages. However, consider it only when advantages are too compelling to omit. <\/span><\/p>\n

Here is one more condition that some disadvantages might be more relevant for a particular use case but not really linked to ours. So, here we are listing out some of the disadvantage associated with Kafka:<\/span><\/p>\n

a. No Complete Set of Monitoring Tools<\/strong>
\nIt is seen that it lacks a full set of management and monitoring tools. Hence, enterprise support staff felt anxious or fearful about choosing Kafka and supporting it in the long run.<\/span><\/p>\n

b. Issues with Message Tweaking<\/strong>
\nAs we know, the broker uses certain system calls to deliver messages to the consumer. However, Kafka\u2019s performance reduces significantly if the message needs some tweaking. So, it can perform quite well if the message is unchanged because it uses the capabilities of the system.<\/span><\/p>\n

c. Not support wildcard topic selection<\/strong>
\nThere is an issue that Kafka only matches the exact topic name, that means it does not support wildcard topic selection. Because that makes it incapable of addressing certain use cases.<\/span><\/p>\n

d. Lack of Pace<\/strong>
\nThere can be a problem because of the lack of pace, while API\u2019s which are needed by other languages are maintained by different individuals and corporates.<\/span><\/p>\n

e. Reduces Performance<\/strong>
\nIn general, there are no issues with the individual message size. However, the brokers and consumers start compressing these messages as the size increases. Due to this, when decompressed, the node memory gets slowly used. <\/span>Also, compress happens when the data flow in the pipeline. It affects throughput and also performance.<\/span><\/p>\n

f. Behaves Clumsy<\/strong>
\nSometimes, it starts behaving a bit clumsy and slow, when the number of queues in a Kafka cluster increases.<\/span><\/p>\n

g. Lacks some Messaging Paradigms<\/strong>
\nSome of the messaging paradigms are missing in Kafka like request\/reply, point-to-point queues and so on. Not always but for certain use cases, it sounds problematic.<\/span><\/p>\n

So, this was all about the advantages and disadvantages of Kafka. Hope you like our explanation.<\/p>\n

Conclusion: Advantages and Disadvantages of Kafka<\/span><\/h2>\n

Hence, we have seen all the Advantages and Disadvantages of Kafka in detail. That will help you a lot before using it. However, if any doubt occurs regarding Kafka Pros and Cons, feel free to ask through the comment section.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

In our last Kafka Tutorial, we discussed Books for Kafka. Today, we will discuss the Advantages and Disadvantages of Kafka. 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