EverythingWill Flow.

FlowMQ unifies MQTT, Kafka, AMQP, and NATS into one platform, connecting devices, agents, apps, and data from edge to cloud.

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MQTT

Kafka

AMQP

NATS

FlowMQ

MQTT

Device Connectivity

Lightweight pub/sub messaging protocol connecting millions of devices.

v5.0 & 3.1.1 native

Kafka

Log Streaming

High-throughput partitioned event streaming for real-time data pipelines.

Distributed commit log

AMQP

Enterprise Queue

Routing exchanges and message queues for legacy enterprise systems.

Flexible routing topology

NATS

Cloud Messaging

Low-latency pub/sub messaging system for cloud-native microservices.

Simple message fabric

The FlowMQ Platform

One data plane. No adapters. No bridges. No glue code. Just seamless data flow.

One Engine

Architect a protocol-agnostic core routing model.

Three Paradigms

Combine pub/sub, queues, and streams.

Four Protocols

Unify MQTT, Kafka, AMQP and NATS.

Any Workload

Handle OT, IT, IoT, and AI workloads.

Multi-Tenancy

Manage brokers for your org in one place.

FlowMQ Architecture

FlowMQ adopts an unbundled architecture that fully decouples metadata services, stateless brokers, and S3-based storage.

MQTTDevices

AMQPQueues

KafkaStreams

NATSPub/Sub

Control Plane

Namespace

Metadata

Coordinator

Security

Stateless Brokers

Broker 1

Broker 2

Broker 3

Data Storage (S3)

AI Agents

Applications

Data Lakes

Cloud Services

Scalable

Decouple metadata, compute, and storage to grow connections and throughput independently.

Limitless

Store unlimited topics, partitions, and queues in cloud object storage with zero disk or metadata constraints.

Stateless

Swap or recover broker nodes automatically in seconds—with zero partition rebalancing or state migration lag.

Elastic

Scale compute dynamically from zero to millions of connections or hundreds of GB/s throughput in seconds.

Deterministic

Deliver guaranteed, predictable ultra-low latency across all protocols using a single-threaded message routing engine.

Efficient

Slash infrastructure TCO by up to 90% with a high-performance C++ core engine and low-cost S3 object storage.

Your Existing Stack, Plugged In.

FlowMQ runs a fully managed cloud service with zero local setup required. Simply connect to our endpoint using the language-native SDKs you already trust.

Publish telemetry over MQTT, produce streams into Kafka partitions, route AMQP enterprise exchanges, and broadcast over NATS subjects — all under one runtime engine.

Explore Our SDK References

mqtt_publish.c

// Publish telemetry to FlowMQ Cloud Broker using Paho C
#include <stdio.h>
#include <string.h>
#include "MQTTClient.h"

int main(void)
{
    const char *url = "tcp://fmq-eef4f84607a04d13.tiger.prod.us-east-1.flowmq.cloud:1883";
    MQTTClient client;
    MQTTClient_connectOptions conn_opts = MQTTClient_connectOptions_initializer;
    MQTTClient_message pubmsg = MQTTClient_message_initializer;
    MQTTClient_deliveryToken token;

    MQTTClient_create(&client, url, "agent-01", 0, NULL);
    conn_opts.username = "token";
    conn_opts.password = "flow_secret_xyz";

    if (MQTTClient_connect(client, &conn_opts) != MQTTCLIENT_SUCCESS)
        return -1;

    pubmsg.payload = "{\"status\":\"active\"}";
    pubmsg.payloadlen = (int)strlen(pubmsg.payload);
    pubmsg.qos = 1;

    MQTTClient_publishMessage(client, "telemetry/agents", &pubmsg, &token);
    MQTTClient_waitForCompletion(client, token, 10000L);

    MQTTClient_disconnect(client, 10000);
    MQTTClient_destroy(&client);
    return 0;
}

// Publish telemetry to FlowMQ Cloud Broker using Paho C
#include <stdio.h>
#include <string.h>
#include "MQTTClient.h"

int main(void)
{
    const char *url = "tcp://fmq-eef4f84607a04d13.tiger.prod.us-east-1.flowmq.cloud:1883";
    MQTTClient client;
    MQTTClient_connectOptions conn_opts = MQTTClient_connectOptions_initializer;
    MQTTClient_message pubmsg = MQTTClient_message_initializer;
    MQTTClient_deliveryToken token;

    MQTTClient_create(&client, url, "agent-01", 0, NULL);
    conn_opts.username = "token";
    conn_opts.password = "flow_secret_xyz";

    if (MQTTClient_connect(client, &conn_opts) != MQTTCLIENT_SUCCESS)
        return -1;

    pubmsg.payload = "{\"status\":\"active\"}";
    pubmsg.payloadlen = (int)strlen(pubmsg.payload);
    pubmsg.qos = 1;

    MQTTClient_publishMessage(client, "telemetry/agents", &pubmsg, &token);
    MQTTClient_waitForCompletion(client, token, 10000L);

    MQTTClient_disconnect(client, 10000);
    MQTTClient_destroy(&client);
    return 0;
}

Dependency: libpaho-mqtt3c

FlowMQ Use Cases

From AI agentic workflows to Kafka replacement and diskless S3 data pipelines.

AI Agents

AI / Agentic

Coordinate AI agents with A2A messaging, workflow orchestration, tool work queues, and S3 reasoning log retention.

A2A · Tool Queues · S3 Context

Kafka Replacement

Core Infra

Replace Kafka with a diskless, S3-based engine that uses no local NVMe/EBS disks or cross-AZ fees—cutting TCO up to 90%.

Diskless · Zero Egress · 90% TCO

Data Lake Ingestion

Analytics

Ingest high-throughput event streams directly into Snowflake, Databricks, ClickHouse, and Iceberg without complex ETL.

Snowflake · Databricks · ClickHouse

IoT & Edge Telemetry

Edge & IoT

Collapse multi-tier MQTT and Kafka architectures into a single engine with native MQTT edge ingestion and Kafka cloud consumption.

MQTT v5 · Edge-to-Cloud · Wildcards

Message & Work Queues

Messaging

Consolidate RabbitMQ and NATS into an S3-backed broker powering unlimited work queues with competing consumers.

RabbitMQ · NATS · Work Queues

Event-Driven Architecture (EDA)

Services

Power resilient, event-driven architectures by unifying microservice decoupling, async RPC, and agentic workflows.

Async RPC · Pub/Sub · Decoupling

Frequently Asked Questions

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