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OpenMessaging

About OpenMessaging

OpenMessaging provides a cloud native, vendor-neutral open specification for distributed messaging. The specification is designed for implementation on clouds with scalability, flexibility, isolation, and security. It does not rely on or favor any business products and supports areas including finance, e-commerce and IoT. It is compatible with multiple platforms including Java, c/c++, go, .net, and python. It enables big data streaming and computation. Wire level protocols such as MQTT, AMQP, and private protocols are implemented to guarantee compatibility.

Used for

  • Decoupling, queuing, buffering, ordering, and replicating data in messaging architectures
  • Connecting different cloud platforms through OMS
  • Facilitating standard benchmark testing
  • Developing messaging and streaming applications across heterogeneous systems and platforms

From OpenMessaging's own website, read 2026-10-24. How we build listings.

How to evaluate Streaming & Real-Time Analytics

This is how the CIOPages Research Team evaluates this category. It is not an assessment of OpenMessaging. It comes from our Streaming Data & Event Processing buyer guide.

25%
Throughput, Latency & Durability
Sustained throughput and tail latency at your partition count, ordering and exactly-once / at-least-once delivery guarantees, replication and multi-AZ durability, retention limits, and behavior under broker failure and rebalancing
20%
Operating Model & Architecture
Self-managed vs. fully managed vs. serverless vs. bring-your-own-cloud, KRaft (post-ZooKeeper) operations, diskless / object-storage-backed options, autoscaling, partition rebalancing, and upgrade and patching burden on your team
20%
Kafka-API Compatibility & Portability
Fidelity of the Kafka protocol (consumer groups, transactions, compaction), reuse of existing clients, connectors and tooling, lock-in to a single cloud, and the realistic effort to migrate in or out
15%
Stream Processing & Ecosystem
Native or integrated processing (Flink, Kafka Streams, Spark Structured Streaming, ksqlDB), connector catalog (CDC, sinks, sources), schema registry and governance, and direct landing into Iceberg / Delta lakehouse tables
10%
Security, Governance & Compliance
Encryption in transit and at rest, mTLS / SASL / OAuth and RBAC, audit logging, private networking, data residency and BYOC data-boundary control, and SOC 2 / ISO 27001 / GDPR coverage
10%
Cost Model & Economics at Scale
Pricing unit (capacity / throughput / consumption), inter-AZ and egress charges, storage and retention cost, processing billed separately, and how the bill behaves as volume, partitions, and connectors grow

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Quick Facts

openmessaging.cloud
CategoryData & Analytics
SubcategoryStreaming & Real-Time Analytics
DeploymentCloud

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