Articles

Understanding the Roles of Zookeeper and Bookkeeper in Pulsar

Although they have some similarities, ZooKeeper and BookKeeper provide different administrative services in Pulsar. This article will help you to understand how ZooKeeper and BookKeeper work, the roles these components play in Pulsar, and the differences between ZooKeeper and BookKeeper, highlighting use cases where each component is particularly useful.

A Crash Course in Distributed Pub-Sub Messaging With Apache Pulsar

Messaging is essential to modern life and how you get things done. So, without messaging, how would the world look? This question may appear far-fetched, but it’s a significant concern for computing. How do you talk to software? What is the mechanism through which software programs communicate with each other? How does software speak to you?

Apache BookKeeper Disk Usage With Apache Pulsar

Theoretical attempts to size up disk space for the Apache BookKeeper cluster backing Apache Pulsar occasionally raises questions of why the BookKeeper uses more space in practice than anticipated. Understanding the factors involved in the disk utilization and possible configuration options is important for more precise capacity planning. Let’s look at the specific factors affecting disk usage. Pulsar side Pulsar uses BookKeeper to persist data to the disk. BookKeeper does not delete the data unless Pulsar “tells” that it is safe to delete.

Comparing Apache Pulsar Streaming and Kafka Streaming

This article examines how Pulsar and Kafka approach streaming by discussing their architectures and services. After briefly reviewing the definition of streaming, we’ll start our discussion with Kafka, since it’s the tool against which all others in the category are compared. We’ll then outline how Pulsar differs from and solves the problems Kafka leaves unaddressed — specifically, how it handles streaming.

Comparing Apache Pulsar and RabbitMQ

Let’s take an in-depth look at the similarities and differences between Pulsar and RabbitMQ

Apache Pulsar Multi Tenancy Explained

Apache Pulsar was built from scratch to focus on multi-tenancy as a founding principle. To manage multi-tenancy aspects within a Pulsar instance, Pulsar supports a concept called tenants.

How Schemas Make the World Go Round

The Apache Pulsar Schema is one of the most critical components of Apache Pulsar, an open-source distributed system messaging and streaming platform. In this article, we’ll explore the role of schemas in data streaming and how JSON, Avro, and Apache Pulsar work together to make edge computing possible.

Where Is the Edge?

This article will explore the edge, how it relates to performance-sensitive devices such as IoT devices, and how Apache Pulsar can get you closer to the edge. But first, you need to understand what — and where — the edge is.

REST Versus Event Driven Architecture - Why It's Time to Switch From Request Based Architecture

This article introduces REST and event-driven architectures and explains why organizations should move to an EDA to maximize customer satisfaction.

Why Managed Apache Pulsar Is the Right Choice

In this article, we’ll explore why and how using a managed Apache Pulsar service saves you time and energy by reducing toil. We’ll explore some partners that offer a Pulsar as a service solution and highlight their strengths and challenges to help you select a managed service to use.

The Difference Between Persistent and Non Persistent Topics in Apache Pulsar

This article will explore what Pulsar topics are, the differences between persistent and non-persistent topics in Apache Pulsar, and review some example use cases for both methods.

Integrating Apache Druid With Apache Pulsar

With companies adopting the event streaming pattern, analytics has to become more “realtime” too. A great database for event analytics is Apache Druid. Druid connects natively to various event streaming systems such as Kafka and AWS Kinesis.

How Pulsar and Kafka Partitions Work (And How They Differ)

Both Pulsar and Kafka aim to increase the amount of data that can be consumed and processed by horizontal scaling — spreading data across many partitions. This is possible thanks to parallel processing, wherein the data producer writes to multiple partitions and the consumer reads them.

How Pulsar Can Help IoT Avoid the Internet - Event Streaming at the Edge

This article explains how performance-sensitive IoT applications can improve their performance with event streaming at the edge using Apache Pulsar.

Do I Have Time to Learn Event Streaming?

In this article, we’ll explore what event streaming is, how it works, and discuss the growing importance of event streaming. Then, we’ll highlight how we can simplify the task of learning event streaming with the help of Apache Pulsar.

Moving from Java Message Service (JMS) to Apache Pulsar

Let’s explore some advantages and challenges of moving from JMS to Pulsar.

Apache Pulsar Versus Apache Kafka

In this article, we’ll evaluate the features, architectures, performance, and use cases of Apache Pulsar versus Kafka, to help you decide which is the better solution for you.

Apache Pulsar Schema versus Schemaless — Who’s the Winner?

In this article, we’ll examine how Pulsar Schemas work and contrast them with schemaless systems to determine the best approach. We’ll also demonstrate how to use Java clients with Pulsar.

Understanding the Differences Between Message Queues and Streaming

Almost any application that requires real-time or near-real-time data processing benefits from having a message queue or streaming data processing component in its architecture. Online food ordering apps, e-commerce sites, media streaming services, and online gaming are straightforward examples. But weather apps, smart cars, health status apps with smartwatch technology, or anything Internet of things (IoT) typically rely on a message queue or streaming engine as well.

Pulsar: Queuing and Streaming - An All in One Messaging System

I would also like to focus this reading on what is Pulsar and how it works under its own merits rather than comparing it against apache Kafka. I am taking this approach as there is plenty literature doing this already and because from a messaging system architecture both of these paradigms, up to a point, are different.

Pulsar: Building a High Available Messaging System - A Step by Step CookBook

This guide will walk you step by step to deploy a Pulsar instance with one cluster but prepared already to extend the deployment further, including more Pulsar clusters at a later stage.