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| Pivotal RabbitMQ | |
|---|---|
| Name | Pivotal RabbitMQ |
| Developer | Pivotal Software |
| Released | 2007 |
| Latest release | 3.x |
| Programming language | Erlang |
| Operating system | Cross-platform |
| License | Mozilla Public License |
Pivotal RabbitMQ Pivotal RabbitMQ is a commercial distribution of the open-source message broker that provides enterprise-grade support, performance tuning, and integration services. It is used to decouple distributed systems, enable asynchronous communication, and support event-driven architectures across cloud platforms, container environments, and virtualized datacenters. Organizations adopt it to connect microservices, integrate legacy systems, and implement messaging patterns for high-throughput, resilient systems.
Pivotal RabbitMQ is a supported packaging of the RabbitMQ broker originally authored in Erlang, associated with implementations in organizations such as VMware and Pivotal Software. It sits within ecosystems that include Cloud Foundry, Kubernetes, OpenStack, Amazon Web Services, and Google Cloud Platform, and is designed to interoperate with libraries and clients for Java, Python (programming language), Go (programming language), .NET Framework, and Node.js. Enterprise offerings augment the broker with lifecycle management, monitoring integrations for Prometheus, Grafana, and logging through ELK Stack, while professional services often coordinate with vendors like Red Hat and Microsoft.
The distribution preserves the underlying Erlang/OTP architecture, leveraging the BEAM (Erlang virtual machine) for concurrency and clustering, and uses the Advanced Message Queuing Protocol family such as AMQP 0-9-1 for client interoperability. Clustering uses mirrored queues and quorum queues to provide replication patterns analogous to systems like Apache Kafka and Redis (software), while federation and shovel plugins enable cross-datacenter topologies similar to patterns used by Cassandra (database) and Consul (software). Management interfaces expose HTTP APIs inspired by RESTful API conventions used by GitHub and Stripe.
Enterprise packages are distributed for platforms including Ubuntu, Debian, Red Hat Enterprise Linux, and Windows Server, and are commonly deployed on virtualization stacks such as VMware vSphere or container orchestrators like Kubernetes. Deployment automation frequently involves tools such as Ansible, Terraform, Puppet (software), and Helm (software), and CI/CD pipelines coordinate with systems like Jenkins and GitLab. Operators often integrate with service meshes like Istio and runtime platforms like Pivotal Cloud Foundry for routing and lifecycle management.
Administrative workflows use the built-in management UI and CLI utilities, and integrate with observability platforms including Datadog, New Relic, and Splunk for telemetry. Configuration files follow Erlang configuration conventions that echo formats seen in PostgreSQL and Nginx, and operational tooling supports rolling upgrades and node maintenance strategies comparable to practices for MongoDB and MySQL. Role-based access and plugin management are administered alongside orchestration frameworks such as Chef and SaltStack.
Capabilities include support for messaging models like publish/subscribe, request/reply, and work queues, comparable to paradigms implemented by ZeroMQ and Apache ActiveMQ. The distribution provides features such as high-availability mirrored queues, quorum queues for strong consistency, plugin extensibility akin to ElasticSearch modules, and protocol adapters for MQTT and STOMP. Performance features include tuning for throughput and latency, monitoring endpoints for metrics collectors like Prometheus, and integration with enterprise service buses found in TIBCO and MuleSoft ecosystems.
Enterprise releases emphasize security hardening with TLS encryption, client authentication mechanisms including LDAP and OAuth 2.0, and authorization models comparable to those used by Kubernetes RBAC and Active Directory. Audit logging and compliance workflows align with standards referenced by organizations such as PCI DSS, ISO/IEC 27001, and SOC 2, and deployments frequently incorporate secrets management via tools like HashiCorp Vault and key management services from AWS Key Management Service and Azure Key Vault.
Common uses include microservices communication in platforms influenced by Netflix and Amazon.com (company), event streaming for analytics pipelines used by LinkedIn and Twitter, task distribution in batch systems similar to implementations at Dropbox and Facebook, and IoT telemetry ingestion via Eclipse Mosquitto and Azure IoT Hub. Integrations span message routing with Spring Framework, data ingestion into Apache Hadoop, and orchestration with Apache Airflow and Kubernetes Operators tailored for messaging workloads.
The broker’s origins stem from open-source efforts in messaging realized in the mid-2000s, developed using Erlang and influenced by messaging research and products from entities such as Yahoo! and Red Hat. Commercial distributions and enterprise support evolved alongside cloud-native platforms from VMware and Pivotal Software, with community contributions coordinated through foundations and repositories like GitHub and standards bodies that steward protocols such as AMQP Working Group. The project’s roadmap has reflected broader industry trends toward containerization, observability, and multi-cloud deployments driven by the rise of Docker, Kubernetes, and large cloud providers such as Amazon Web Services.
Category:Message brokers