Apache Pulsar combines the best features of a traditional messaging system like Apache Kafka and a queuing system like RabbitMQ. It’s a cloud-native, multi-tenant, high-performance system that performs server-to-server messaging, streaming, and queuing.
With high performance, geo-replication for reduced latency, and three-in-one streaming, queuing, and messaging features, many organizations use Apache Pulsar for their distributed messaging and streaming service needs.
Although Pulsar is open-source and configurable from scratch, it can be complicated and overwhelming to get started with, as every area of the software needs configuration. Additionally, its setup process requires specialized and expert messaging experts, which are expensive to hire and retain, thereby increasing costs.
Though distributed messaging and streaming services are more important to software than ever, setting up and maintaining such systems can be extremely complex. This may lead you to believe that utilizing tools like Apache Pulsar is out of your reach without significant investment.
However, managed Pulsar service options — referred to as Pulsar as a service — can provide you with the capabilities of Apache Pulsar without going through the trouble of hiring Pulsar experts, setting up a custom environment, and dealing with the ongoing toil of maintaining a complex Pulsar environment.
Say, for example, your organization has a messaging system that sends out occasional marketing messages (via email, SMS, and in-app), updates, and discount information to loyal customers. This messaging system can become quite complex to manage as your customer base grows and communication channels expand. To handle these challenges, you can incorporate a managed Pulsar service into your messaging architecture to have an efficient message and distribution process — one that can handle this complexity.
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.
Choosing a Managed Apache Pulsar Service
There are several managed Apache Pulsar services on the market. When determining which provider to work with, you should consider the following:
- Support — Errors may occur during the configuration and implementation of Apache Pulsar. An effectively managed Pulsar solution should provide 24/7 support to help with implementation errors and bugs.
- Performance reliability — Since most organizations rely on continuous streaming and uptime to make decisions, a Pulsar as a service solution should guarantee a minimum of 99.99 percent uptime.
- Latency — Ensuring messages and queries get processed quickly is essential for streaming platforms, as the faster query processing occurs, the quicker the performance. Be conscious of latency and its potential impact on your business.
- Multi-cloud availability — Today, most businesses are built on the cloud, or work with the cloud in some capacity. Ensuring that your Pulsar managed service deploys to any popular cloud solution, like Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP) makes for easier business integrations.
- Costs — Most managed Apache Pulsar solutions provide pricing models like pay as you go (PAYG) or on-demand, reserved pricing.
- PAYG pricing ensures you only pay for what you consume, leaving little room for wastage of resources and reduced cost.
- On-demand pricing ensures resources are available when needed, and organizations pay a flat rate depending on the consumption of resources. Although this type of pricing provides easy scaling up/down resources and reduces wastage, it typically works best for short-term workloads, and it can become expensive.
- Reserved instances work for long-term workloads and can help reduce costs over time, as longer time commits and advanced payment usually results in discounted fees for provisioning resources. However, reserved pricing may sometimes result in underutilization and wastage of resources.
Managed Pulsar services that are currently on the market include Pandio, Dattell, Kesque, StreamNative, and DataStax Astra Streaming. Let’s explore each of these Pulsar as a service providers, their benefits, and some challenges they present.
Pandio offers a fully-managed, distributed-messaging service built on Pulsar with quick and efficient performance that’s optimized using artificial intelligence (AI). It provides a latency under 10 milliseconds at a massive scale and can distribute up to two million messages per second per partition. In addition, it offers flexible cloud or on-premise deployments.
Here are some best features of Pandio:
- Pandio offers a service level objective (SLO) of at least 99.99 percent uptime, ensuring uninterrupted business operations.
- It employs the best security measures like encryption at rest/in transit, authentication, and authorization to ensure safety.
- Pandio ensures the increased availability of its messaging service through proper configuration, management, and deployments at each stage.
- By integrating a neural network with Apache Pulsar, Pandio offers predictions using AI and enables organizations to make quick decisions in real time.
Because Pandio offers a fully managed Pulsar service, you may have little to no control over your messaging service. Also, running long-term workloads may become more expensive with the PAYG model.
Developed by the original developers of Apache Pulsar, StreamNative provides a fully-managed, highly-available, and scalable Apache service for diverse business use cases.
StreamNative supports multi-tenancy, allowing infrastructure sharing and leaving organizations with no operational costs.
Other features offered by StreamNative include:
- It uses Pulsar functions to process, filter, and route messages.
- It offers powerful stateful stream processing powered by Apache Flink SmartNoise SQL (SNSQL).
- Authentication measures are in place to ensure security.
- StreamNative supports deployment to cloud solutions like AWS and GCP, with support for Azure still in beta stages.
StreamNative provides three pricing plans: free, cloud-hosted, and cloud-managed plans. It also utilizes an on-demand pricing model depending on cluster size and traffic.
Note that StreamNative currently only provides support for AWS and GCP cloud services, with support for Azure still in beta. If you use Azure as your cloud provider, you may find StreamNative isn’t the best choice for you. Additionally, the on-demand pricing model of StreamNative may quickly become expensive as clusters increase.
Dattell draws on Kafka, Elasticsearch, and OpenSearch to enable you to build reliable, secure, automated, and usable architecture.
Dattall offers the following benefits:
- To remain secure and stable, Dattell provides audits of ongoing architecture implementation and helps fix issues.
- A fully managed Pulsar environment with a guaranteed 99.999 percent uptime.
- It provides regular preventative maintenance and customization of your clusters and trains your staff to become Pulsar experts.
Dattell optimizes its clusters manually, which may introduce human-prone errors to its deployments.
DataStax Astra Steaming
Astra Streaming is DataStax’s next-generation, managed Pulsar streaming solution. Built on Pulsar, Astra Streaming allows you to create streaming, responsive applications on a highly stable, multi-cloud messaging and streaming platform.
Here are some key features of Astra Streaming:
- Existing AstraDB customers can build streaming data pipelines with Astra Streaming since it’s a compliment that comes with AstraDB.
- Organizations can build and deploy their streaming solutions on any of the most popular cloud service providers, like AWS, Azure, and GCP are compatible with Pulsar, providing multi-cloud availability.
- DataStax provides real-time monitoring of the overall health of your clusters using Pulsar Heartbeat. This feature is a preventive approach to identifying and handling failures or unavailability and gives you visibility into the state of your clusters.
- There are several business use cases for Astra Streaming, like elevated digital experiences, powering the massive event streams from Internet of Things (IoT) devices, and providing business key holders with real-time analytics to enable more intelligent business decisions.
For organizations looking to run a managed Pulsar service but on-premises, DataStax provides its DataStax Luna Streaming option, a production-level distributed version of Pulsar.
Like other PAYG pricing models, running costs may become expensive for long-term workloads. You will want to be cautious of how you’re using resources and the size of your workload, even with DataStax.
Apache Pulsar is a messaging, streaming, and queuing solution that helps organizations build fast, responsive applications. Its multi-cloud architecture, improved performance, and geo-location replication features make it an excellent choice for building scalable and reliable business-ready solutions.
However, the configuration and implementation of Apache Pulsar can be complex and expensive, requiring specialized Pulsar experts and a significant amount of time. To bypass these costs and simplify the process of getting started with Apache Pulsar, you can use a managed Apache Pulsar service.
In this article, we looked at popular Pulsar as a service providers, including Pandio, StreamNative, Kesque, Dattell, and DataStax’s Astra Streaming. Each of these solutions has valuable features, challenges that accompany using them, and different pricing models.
As you select which Pulsar as a service model to use, be sure to consider things like cost, the availability of support, latency, and multi-cloud availability. With distributed messaging and streaming becoming increasingly foundational to the development process, now’s the right time to get started with a managed Apache Pulsar service.