What is
Apache Pulsar?
Modern data-driven applications need nimble and scalable distributed messaging and event streaming that won’t fail. Open source Apache Pulsar was designed for just that, offering real-time data processing and messaging at scale for cloud-native teams. Here’s a deep dive into the role Apache Pulsar can play in modern application development and delivery and why it’s the solution of choice for organizations that make customer service a priority.
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Understanding Apache Pulsar
To put it simply, no one wants to wait on an application. So the longer the processing time, the more likely a customer is going to bail, switch, or just give up in frustration - and that’s a reality software development teams ignore at their peril. The solution is to build in truly scalable and fault tolerant support for messaging and event streaming, all while getting to market quickly and keeping costs in check. Other microservices options - including Apache Kafka and RabbitMQ - attempt to address these issues, but both have critical limitations that don’t exist in Apache Pulsar.
The design of Apache Pulsar sets it apart from traditional messaging systems. Apache Pulsar separates message storage from message serving, allowing for easy horizontal scaling and low-latency message delivery. This means that Pulsar can efficiently serve large numbers of subscribers while ensuring messages are durably stored, even during temporary disconnections.
At the heart of Apache Pulsar's architecture is a publish-subscribe model. Data is organized into "topics," which act as communication channels. Publishers can send messages or events to these topics, and subscribers can receive the data in real-time. This architecture enables seamless communication between various components and services.
Inside Apache Pulsar
Apache Pulsar brings numerous features to the table, including:
Scalability
Apache Pulsar is highly scalable, and it can effortlessly handle an increasing number of topics and subscribers without compromising performance.
Multitenancy
It offers efficient and secure resource sharing between different teams or applications with isolated access controls.
Persistent Storage
Messages are durably stored, providing reliability and preventing data loss, even if subscribers are offline.
Georeplication
Pulsar supports cross-datacenter replication, enhancing disaster recovery and data locality.
Message Batching
Pulsar optimizes message delivery through efficient batching, reducing overhead and improving overall performance.
Pluggable Authentication
It offers flexible authentication and authorization mechanisms to meet varying security requirements.
Apache Pulsar is highly scalable, and it can effortlessly handle an increasing number of topics and subscribers without compromising performance.
Pulsar offers efficient and secure resource sharing between different teams or applications with isolated access controls.
Messages are durably stored, providing reliability and preventing data loss, even if subscribers are offline.
Pulsar supports cross-datacenter replication, enhancing disaster recovery and data locality.
Pulsar optimizes message delivery through efficient batching, reducing overhead and improving overall performance.
It offers flexible authentication and authorization mechanisms to meet varying security requirements.
Built by the original creators of Apache Pulsar, StreamNative Cloud brings speed and peace of mind to your could-native application projects.
Common Pulsar use cases
Event-Driven architecture
To make applications scalable and manageable, teams break down large monolithic applications into smaller services. Cloud-based Apache Pulsar is the ideal technology to be the central nervous system of your applications. Zhaopin, one of the largest career platforms in China, switched to Pulsar for better performance while reducing cost and complexity.
Event Sourcing
To provide a 100% reliable audit log, architects create a pattern of events as the source of truth for a business entity. This pattern allows for calculating states at any given time and the ability to update business rules and reapply them retroactively from the events log. Pulsar supports millions of topics, which can be individually dedicated to business entities. Orange Financial is leveraging Apache Pulsar’s broad ability to handle topics to help combat fraud.
Geo-replication
Geo-replication is a native feature of open-source Apache Pulsar that replicates data across multiple regions or geographical locations for disaster recovery, reduced latencies, or increased data durability in real-time. It allows organizations to maintain business continuity and prevent data loss in the event of a disaster, network failure or other issue in one of the operated regions. Intelligent speech and AI recognition provider iFLYTEK leaned into Pulsar’s Geo-replication strength (among other things) for its message queue system.
Data Pipelines
Pulsar's capability to handle massive data streams makes it ideal to create data pipelines for fraud detection, real-time personalization, real-time analytics, ETL (Extract, Transform, Load), machine learning, and Internet of Things (IoT). Seoul-based fintech company Qraft chose Pulsar to power its AI-based products because of its low latency and high throughput.
Message Queues
Message queues enable applications to communicate with each other asynchronously by passing messages between them. Message queues are used to decouple applications, improve scalability, handle data throughput spikes or to increase reliability by ensuring that communication is not lost when a component fails. GeTui is a large push notification provider that switched from Kafka to Pulsar to get better support for message queues.
Compare Pulsar to other microservices
Pulsar vs. Apache Kafka
Apache Kafka is another popular messaging system that has been widely adopted for microservices. While Kafka has its strengths, there are key differences when compared to Apache Pulsar.
Data Retention and Message Offsets
Kafka retains messages for a specified time, while Pulsar retains data based on configurable policies. Pulsar's message offset management allows fine-grained control over data retention, optimizing storage usage.
Partition Rebalancing
Kafka's partition rebalancing process can cause temporary interruptions during scaling or failure recovery. Pulsar's architecture avoids such disruptions and offers smoother scaling.
Pulsar vs. RabbitMQ
RabbitMQ is a widely-used traditional messaging system. While it may be suitable for some microservices scenarios, there are significant distinctions compared to Apache Pulsar.
Message Durability
Pulsar's persistent storage ensures messages are durably stored, even if subscribers are offline. RabbitMQ may lose messages during broker restarts if not explicitly marked as durable.
Scalability
Pulsar's architecture inherently supports scaling, whereas RabbitMQ may require additional configurations for handling growing workloads.
Want to learn more about Apache Pulsar?
Built by the original creators of Apache Pulsar, StreamNative is the place to begin.
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