List of the Top 11 Event Brokers for New Relic in 2025

RabbitMQ serves as a nimble messaging solution that can be easily implemented in both on-premises setups and cloud-based environments. Its support for multiple messaging protocols renders it a flexible choice for a variety of applications. Additionally, RabbitMQ can be set up in distributed and federated configurations to meet the needs for high scalability and robust availability. With a large community of users, it is recognized as one of the top open-source message brokers currently available. Companies ranging from T-Mobile to Runtastic utilize RabbitMQ, demonstrating its suitability for both burgeoning startups and established enterprises alike. Moreover, it is designed to work seamlessly across a multitude of operating systems and cloud platforms, providing a rich array of development tools tailored for popular programming languages. Users can take advantage of deployment options including Kubernetes, BOSH, Chef, Docker, and Puppet, which enables smooth integration into their current environments. Developers also have the ability to craft cross-language messaging solutions using a selection of programming languages such as Java, .NET, PHP, Python, JavaScript, Ruby, and Go, thereby broadening its applicability across diverse projects. Ultimately, RabbitMQ’s versatility and compatibility make it an essential tool for modern software development.

Apache Kafka® is a powerful, open-source solution tailored for distributed streaming applications. It supports the expansion of production clusters to include up to a thousand brokers, enabling the management of trillions of messages each day and overseeing petabytes of data spread over hundreds of thousands of partitions. The architecture offers the capability to effortlessly scale storage and processing resources according to demand. Clusters can be extended across multiple availability zones or interconnected across various geographical locations, ensuring resilience and flexibility. Users can manipulate streams of events through diverse operations such as joins, aggregations, filters, and transformations, all while benefiting from event-time and exactly-once processing assurances. Kafka also includes a Connect interface that facilitates seamless integration with a wide array of event sources and sinks, including but not limited to Postgres, JMS, Elasticsearch, and AWS S3. Furthermore, it allows for the reading, writing, and processing of event streams using numerous programming languages, catering to a broad spectrum of development requirements. This adaptability, combined with its scalability, solidifies Kafka's position as a premier choice for organizations aiming to leverage real-time data streams efficiently. With its extensive ecosystem and community support, Kafka continues to evolve, addressing the needs of modern data-driven enterprises.

A Unified Platform for Instant Communication: An innovative solution designed for creating and managing real-time interactions across web, mobile, AI/ML, IoT, and edge computing applications. Streamlined and Accelerated Deployments: With SDK compatibility for over 50 environments including mobile, web, server, and IoT (supported by both PubNub and the community), alongside more than 65 ready-made integrations with various external and third-party APIs, the platform ensures you have access to essential features, irrespective of your programming language or technology stack. Unmatched Scalability: Recognized as the most scalable platform in the industry, it can effortlessly accommodate millions of simultaneous users, ensuring rapid expansion with minimal latency and high uptime, all without incurring financial penalties, making it a reliable choice for growing businesses. Furthermore, this platform is designed to evolve with your needs, supporting future advancements in technology seamlessly.

Leverage Service Bus to establish a reliable cloud messaging framework that enables seamless interaction between various applications and services, even when they are offline. This fully managed offering is available across all Azure regions, eliminating the burden of server maintenance and licensing issues. With its support for asynchronous operations, you will gain improved flexibility in managing communication between clients and servers, enhanced by features such as structured first-in, first-out (FIFO) messaging and a publish/subscribe model. By taking advantage of asynchronous messaging patterns, your enterprise applications can scale efficiently to meet demand. Moreover, you can easily integrate cloud services like Azure SQL Database, Azure Storage, and Web Apps with Service Bus messaging to ensure consistent performance during varying workloads, all while sustaining resilience against temporary disruptions. To further enhance system availability, design intricate messaging topologies that incorporate advanced routing capabilities. Additionally, harness the power of Service Bus to facilitate effective message dissemination to multiple subscribers, allowing for extensive message distribution to downstream systems on a grand scale. This strategic approach empowers organizations to uphold operational efficiency while addressing their diverse communication requirements, ensuring they remain agile in an ever-evolving digital landscape.

A large volume of data can be transmitted as messages among various services, applications, and systems simultaneously. In the event of an application becoming unavailable or experiencing service disruptions, there is a risk that messages and transactions might either be lost or duplicated, which could lead to significant financial and time-related implications for businesses. Over the last quarter-century, IBM has enhanced IBM MQ, a robust solution that ensures messages are retained in a queue until they are successfully delivered. This platform guarantees that data, including file data, is transferred only once to prevent competitors from sending messages redundantly or at incorrect times. With IBM MQ, the assurance is that no message will ever be lost. IBM MQ is versatile and can be deployed on mainframes, within containers, or across public and private cloud environments. Additionally, IBM provides an IBM-managed cloud service known as IBM MQ Cloud, which is hosted on platforms like Amazon Web Services or IBM Cloud, alongside a specialized hardware solution called IBM MQ Appliance, designed to streamline the deployment and upkeep processes. This flexibility enables businesses to tailor their messaging solutions to their specific infrastructure needs.

Amazon Simple Queue Service (SQS) is a completely managed messaging solution designed to support the decoupling and scalability of microservices, distributed systems, and serverless applications. It simplifies the complexities and management challenges typically associated with traditional message-oriented middleware, enabling developers to focus on their primary responsibilities. With SQS, users can efficiently send, store, and receive messages across various software components at any scale, ensuring that no messages are lost and that dependent services can remain inactive. Getting started with SQS is a breeze, as users can employ the AWS console, Command Line Interface, or their favorite SDK to carry out just three straightforward commands. This service allows for the transmission of substantial data volumes with high throughput, while preserving message integrity and ensuring independence from other services. Furthermore, SQS plays a crucial role in decoupling application components, which allows them to function and fail independently, thereby significantly improving the overall fault tolerance and reliability of the system. By utilizing SQS, applications can achieve enhanced resilience and efficiency in managing messaging tasks, ultimately leading to improved performance and user satisfaction. Adopting SQS can transform how applications handle communication, making them more robust and adaptable to changing conditions.

Amazon Simple Notification Service (SNS) serves as an all-encompassing messaging platform tailored for both inter-system and application-to-person (A2P) communications. It enables seamless interaction between different systems through publish/subscribe (pub/sub) techniques, fostering communication among independent microservices as well as direct engagement with users via channels such as SMS, mobile push notifications, and email. The pub/sub features designed for system-to-system communication provide topics that enable high-throughput, push-based messaging for numerous recipients. By utilizing Amazon SNS topics, publishers can efficiently send messages to a diverse range of subscriber systems or customer endpoints, including Amazon SQS queues, AWS Lambda functions, and HTTP/S, which supports effective parallel processing. Additionally, the A2P messaging functionality empowers you to connect with users on a broad scale, offering the flexibility to either use a pub/sub model or send direct-publish messages via a single API call. This versatility not only enhances the communication process across various platforms but also streamlines the integration of messaging capabilities into your applications.

Google Cloud Pub/Sub presents a powerful solution for efficient message delivery, offering the flexibility of both pull and push modes for users. Its design includes auto-scaling and auto-provisioning features, capable of managing workloads from zero to hundreds of gigabytes per second without disruption. Each publisher and subscriber functions under separate quotas and billing, which simplifies cost management across the board. Additionally, the platform supports global message routing, making it easier to handle systems that operate across various regions. Achieving high availability is straightforward thanks to synchronous cross-zone message replication and per-message receipt tracking, which ensures reliable delivery at any scale. Users can dive right into production without extensive planning due to its auto-everything capabilities from the very beginning. Beyond these fundamental features, it also offers advanced functionalities such as filtering, dead-letter delivery, and exponential backoff, which enhance scalability and streamline the development process. This service proves to be a quick and reliable avenue for processing small records across diverse volumes, acting as a conduit for both real-time and batch data pipelines that connect with BigQuery, data lakes, and operational databases. Furthermore, it can seamlessly integrate with ETL/ELT pipelines in Dataflow, further enriching the data processing landscape. By harnessing these capabilities, enterprises can allocate their resources towards innovation rather than managing infrastructure, ultimately driving growth and efficiency in their operations.

Amazon MQ is a managed message broker service in the cloud, specifically tailored for Apache ActiveMQ, which streamlines the setup and management of message brokers. It allows for smooth communication and data sharing between diverse software systems that may run on various platforms and employ different programming languages. By taking care of the provisioning, configuration, and continuous upkeep of ActiveMQ, Amazon MQ significantly reduces the operational workload for users. The service integrates seamlessly with existing applications by utilizing commonly accepted APIs and messaging protocols, including JMS, NMS, AMQP, STOMP, MQTT, and WebSocket. This commitment to industry standards generally facilitates an easy transition to AWS without needing significant changes to current messaging code. Users can quickly provision their message broker through a few clicks in the Amazon MQ Console, gaining access to version updates and ensuring they always use the latest version supported by Amazon MQ. Once the broker is set up, applications are primed to efficiently produce and consume messages as necessary, fostering a strong messaging environment. The combination of user-friendliness and high efficiency makes Amazon MQ an attractive option for organizations aiming to bolster their messaging capabilities in the cloud. Moreover, the flexibility and reliability of the service empower businesses to focus more on innovation and less on infrastructure management.

Amazon Managed Streaming for Apache Kafka (Amazon MSK) streamlines the creation and management of applications that utilize Apache Kafka for processing streaming data. As an open-source solution, Apache Kafka supports the development of real-time data pipelines and applications. By employing Amazon MSK, you can take advantage of Apache Kafka’s native APIs for a range of functions, including filling data lakes, enabling data interchange between databases, and supporting machine learning and analytical initiatives. Nevertheless, independently managing Apache Kafka clusters can be quite challenging, as it involves tasks such as server provisioning, manual setup, and addressing server outages. Furthermore, it requires you to manage updates and patches, design clusters for high availability, securely and durably store data, set up monitoring systems, and strategically plan for scaling to handle varying workloads. With Amazon MSK, many of these complexities are mitigated, allowing you to concentrate more on application development rather than the intricacies of infrastructure management. This results in enhanced productivity and more efficient use of resources in your projects.

Event Hubs is a comprehensive managed service designed for the ingestion of real-time data, prioritizing ease of use, dependability, and the ability to scale. It facilitates the streaming of millions of events each second from various sources, enabling the development of agile data pipelines that respond instantly to business challenges. During emergencies, its geo-disaster recovery and geo-replication features ensure continuous data processing. The service integrates seamlessly with other Azure solutions, providing valuable insights for users. Furthermore, existing Apache Kafka clients can connect to Event Hubs without altering their code, allowing a streamlined Kafka experience free from the complexities of cluster management. Users benefit from both real-time data ingestion and microbatching within a single stream, allowing them to focus on deriving insights rather than on infrastructure upkeep. By leveraging Event Hubs, organizations can build robust real-time big data pipelines, swiftly addressing business challenges and maintaining agility in an ever-evolving landscape. This adaptability is crucial for businesses aiming to thrive in today's competitive market.