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Pulsar Service — Proven Messaging Queue & Unified Streaming
Production-proven Pulsar messaging queue — multi-tenant, geo-replicated, and lakehouse-native.
Proven messaging backbone
Built on Apache Pulsar, battle-tested in mission-critical environments.
Unified queues & streams
Queueing, pub/sub, and streaming in one model — no separate products.
Modernization-ready
Replace legacy MQs, JMS, and Kafka in one service.
• OVERVIEW
The messaging queue and streaming fabric for enterprise modernization
Legacy estates usually have a patchwork of message queues, JMS brokers, Kafka clusters, and custom glue. Each team picks their own, and modernization stalls under the weight of integration and operations. Pulsar Service gives you a single, modern messaging backbone.
A proven messaging queue
For high-value transactional and workflow workloads.
A unified semantics model
That also supports pub/sub and streaming from the same API.
A cloud-native architecture
That scales to millions of topics and many tenants.
A direct on-ramp to the lakehouse
And, when you're ready, to agentic AI with Orca.
• CAPABILITIES
What you get with Pulsar Service
A messaging queue that's also a streaming system—purpose-built for today's enterprise modernization.
A production-proven messaging queue
Durable, replicated storage with strong ordering guarantees. DLQs and retry policies for safe failure handling. Low-latency delivery even under bursty workloads.
Unified messaging & streaming in one API
Queues via shared/failover subscriptions, pub/sub via multiple independent subscriptions, and streaming via long-lived ordered event streams—all from the same primitive.
Multi-tenant, elastic, and geo-replicated
Tenants and namespaces for isolation. Stateless brokers with decoupled storage — scale without rebalancing.
Lakehouse-native by design
Pulsar topics tier to object storage in Iceberg/Delta formats. Queue and stream data becomes queryable tables for BI and ML without separate ETL.
Ready for agents and automation
Agents can observe Pulsar topics—events, tasks, signals—in real time. They act through tools under policy, with every message and action logged.
A production-proven messaging queue
Durable, replicated storage with strong ordering guarantees. DLQs and retry policies for safe failure handling. Low-latency delivery even under bursty workloads.
Unified messaging & streaming in one API
Queues via shared/failover subscriptions, pub/sub via multiple independent subscriptions, and streaming via long-lived ordered event streams—all from the same primitive.
Multi-tenant, elastic, and geo-replicated
Tenants and namespaces for isolation. Stateless brokers with decoupled storage — scale without rebalancing.
Lakehouse-native by design
Pulsar topics tier to object storage in Iceberg/Delta formats. Queue and stream data becomes queryable tables for BI and ML without separate ETL.
Ready for agents and automation
Agents can observe Pulsar topics—events, tasks, signals—in real time. They act through tools under policy, with every message and action logged.
• USE CASES
What You Can Build
Modernize legacy messaging & MQ
Take a phased path from JMS, MQ, RabbitMQ, SQS and bespoke brokers to one cloud-native, multi-tenant messaging service—retiring old infra as you go.
Mission-critical transactional messaging
Use Pulsar Service wherever reliability really matters—payment and settlement flows, order management, inventory updates, and core internal events that must be delivered once and logged forever.
Async workflows and microservices
Replace call chains with event-driven flows. Services publish domain events to Pulsar topics, worker pools consume from shared subscriptions, and DLQs capture failures for later replay.
Messaging backbone for agentic AI
Streams of events become observations for agents, queue-like patterns represent tasks and tool invocations, and lakehouse tables are the long-term memory for training and analysis.
• SUCCESS STORIES
Proven in Production
StreamNative is built for teams at the intersection of real-time systems, data, and AI initiatives.
FAQs
Because Pulsar gives you proven messaging queue capabilities and unified streaming semantics in one system. That lets you consolidate multiple legacy MQs, JMS brokers, and streaming add-ons into a single, cloud-native service—without losing the reliability you depend on.
Pulsar Service is your Pulsar API entrypoint, running on the Ursa engine and optimized for multi-tenant messaging and unified queue/stream patterns. Kafka Cluster (powered by Ursa) is your native Kafka entrypoint, also running on the Ursa engine and focused on lakehouse-native Kafka streaming. They share the same platform and lakehouse integration; you choose the API that matches each workload and migration path.
If you already use Pulsar, you mostly update endpoints and auth. If you're coming from legacy MQs or JMS, you can adapt flows incrementally—pattern by pattern—while Pulsar Service runs alongside your existing systems during migration.
Yes. Pulsar Service runs on the Ursa engine, which writes every event directly to object storage in open Iceberg or Delta Lake format. Your Pulsar topic data is simultaneously available as a lakehouse table — no connectors, no ETL pipelines, no separate copy. That turns what used to be "just queue data" into first-class analytics and ML inputs.
Pulsar Service includes 99.95% uptime SLA for single-zone deployments and 99.99% for multi-zone, with 24/7 support from the Pulsar experts at StreamNative. Production best practices — monitoring, alerting, capacity management — are built in, so you get a messaging and streaming fabric you can standardize on across teams.
Start modernizing with Pulsar Service
- Create your first Pulsar Service cluster.
- Move a single flow (e.g., one queue or one set of events) to Pulsar.
- Expand as you retire legacy MQs and brokers, and connect to your lakehouse and, later, Orca.