Apache Kafka vs Apache Pulsar: Top Differences

Many people have heard about Apache Kafka as well as Apache Pulsar, they both seem like they are the same but once we try to understand the core concepts of both of these software and take a look at their features then we understand that there are many differences between this two software so let’s take a look at the difference between Apache Kafka and Apache Pulsar to understand this.

What is Apache Kafka?

Apache Kafka is known as an event streaming platform that is based on the concept of open source. Kafka is very popular and widely accepted in the software industry because it can handle and process trillions of actions daily along with the processing of events streams and a permanent storage facility.

This is why Kafka is widely used for event streaming by many organizations and some repeated stock exchanges as well Kafka has been downloaded more than five million times which makes it a great choice for developing software that requires handling billions or even trillions of events per day.

Key Features of Kafka:

1. Real-time processing: Apache Kafka offers the feature of real-time processing because it has low latency and offers a high throughput as well. Kafka uses a pub-sub model in which users can subscribe to receive the data.

2. Durability: Kafka holds the data in the form of various brokers which helps in case there is a data segment loss. if one broker which holds the data is offline then other brokers can serve the data.

3. Scalability: Kafka allows for horizontal scaling of the servers which helps in the addition of servers whenever required, this means that whenever new servers are added then the servers still remain online.

4. Lesser latency: Low latency is also one of the features offered by Apache Kafka, low latency helps in the writing and reading of the data in the servers with less time. it is possible to achieve less latency in Apache Kafka because it uses a distributed architecture.

Use Cases of Apache Kafka:

• Used in building real-time streaming data applications.
• Used for website traffic tracking.
• Used in the tracking of user activity.
• Also used for log aggregation in applications.

What is Apache Pulsar?

Apache Pulsar is also developed on the concept of open source but it is a distributed messaging system if we take a look at the history of Apache Pulsar, it was originally designed as a queuing system but in recent updates and releases, it has added many features such as event streaming, etc pulsar uses Apache Bookkeeper to manage its storage layer and also shares the property of Apache Kafka as well as the RabbitMQ.

Apache Pulsar uses Apache Bookkeeper for managing its storage layer which Yahoo developed as a solution to Hadoop’s HDFS namenode. It is a cloud-native platform that supports messaging and streaming and it is designed for the modern distributed system it includes various features such as multi-tenancy, scalability, and handling large distributed systems.

Key Features of Apache Pulsar:

1. Support for 1M topics: Apache pulsar can be scaled horizontally as well if there is an increase in the load of the servers, it also separates the storage for managing the spike that occurs in traffic.

2. Automatic Load Balancing: We can add and remove the nodes in Apache pulsar and the Pulsar will automatically bundle the load balance topic, pulsar also splits the bundles if required and helps to distribute it to the brokers accordingly.

3. K8s Ready: Pulsar was designed for K8 which stands for Kubernetes and its clustering, it is built while keeping in mind the concept of cloud. As pulsar is designed to be stateless it can scale up quickly as well.

4. Geo-Replication: Apache Kafka helps in geo-replication so if there is an outage at a specific data center the data can be easily replicated with other geo-locations available. this helps to reduce the downtime in case of server outage.

Use Cases of Apache Pulsar:

• Cisco IoT control center uses the Apache pulsar for the management of their systems and overall center.
• It can be used in hybrid data architecture and distributed systems when it is required to process real-time streaming data.
• Flipkart also uses Apache Pulsar for efficient management of their systems by integrating the pipelining and throughput management using Apache Pulsar.
• Pulsar is also used for the management of real-time user data analytics in applications.

Comparison Between Apache Kafka and Apache Pulsar

Apache Kafka and Apache Pulsar are popular frameworks used for application development, let’s look at the differences between the two and which one is better under which circumstances.

1. Throughput: Apache Kafka is based on the distributed log for commits and uses a partitioned log for designing where the messages are stored in the form of topics and it is also distributed in the form of clusters but in pulsar, the topics and partitions are served as a separate type of entities which separates the storage and the computation layers.

2. Storage Architecture: Both the tools are used as distributed messaging systems but have some different storage architecture, kafka is based on the model of commit log in which messages are stored in topics but in pulsar these messages are served in the form of partitions and topics which means that pulsar has separate entity.

3. Latency: When we compare the latency between these two services then we can say that Apache Pulsar normally offers lesser latency as compared to Apache Kafka, this is because it has an architecture that computes and stores data separately.

4. Components: We can say that Apache Pulsar and Apache Kafka both contain similar types of components such as brokers, producers, and partitions but the Pulsar also has additional components such as bookies for storage, etc.

5. Message Consumption Model: Apache Kafka uses a traditional pull-based model for the consumption of the message, but in Pulsar, a more advanced model is used which is a push-based model and in this messages are actively pushed from the brokers to the consumers.

Difference Between Apache Kafka and Apache Pulsar

Apache Kafka	Apache Pulsar
It works on the publish-subscribe messaging system.	It works on both the publish-subscribe and queueing messaging systems.
Apache Kafka supports log-structured storage with retention policies.	Apache Pulsar also supports log-structured storage with retention policies.
Apache Kakfa offers very limited multi-tenancy support.	Apache Pulsar offers native multi-tenancy support.
Apache Kafka is configurable, but not as configurable as Apache Pulsar.	Apache pulsar offers highly configurable message TTL settings.
Apache Kafka partitions the messages into topics.	Apache pulsar partitions topics into namespaces, which can contain topics.
Apache Kafka can be complex, and it typically requires manual configuration.	Apache pulsar is good as it supports native support for automatic horizontal scaling.
Apache Kafka works on Apache Kafka Protocol.	Apache Pulsar works on Pulsar Protocol, and Kafka Protocol (compatibility layer).
It has built in support for schema registery.	It has a built-in schema registry to support for schema evolution.
It has good client library support for various programming languages.	Apache Pulsar also has similar rich client library support.

Conclusion

While Apache Kafka and Apache Pulsar have many similar basic components, there are still some major differences in their complexity, flexibility, As, and working. As we discussed in the differences Apache Pulsar is good because it supports natively automatic horizontal scaling whereas Apache Kafka requires manual configuration at some point. Differentiating between Apache Kafka and Apache Pulsar can help us to understand which software we should choose for building our software projects.