Arroyo - Real-Time SQL Stream Processing Engine

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## Arroyo - SQL Stream Processing Engine

Arroyo is a distributed stream processing engine that lets you express real-time data logic as SQL queries and run them as stateful, fault-tolerant pipelines. This AMI delivers a fully configured, secure single-node deployment so you can go from launch to a running pipeline in minutes - no manual installation, no dependency troubleshooting, and no proxy configuration required.

## Who This Is For

Data engineers and platform teams already running Kafka, Kinesis, or other brokers on AWS who need a processing layer without hiring dedicated streaming infrastructure staff. If your team writes SQL but does not want to build and operate bespoke streaming applications, Arroyo lets you ship pipelines with the skills you already have.

## Example Use Case: Real-Time IoT Fleet Monitoring

An operations team ingests sensor readings from an MQTT broker into Arroyo, applies a 1-minute tumbling window aggregation in SQL, joins the result with a device-metadata table, and sinks anomaly alerts to a Kafka topic consumed by a dashboard. The entire pipeline is authored in the browser-based console, previewed live, and promoted to production with a single click - no JVM tuning, no custom code deployment.

## What You Get Out of the Box

• Ready in minutes - Launch the instance, SSH in to read your unique credentials, open the console on port 80, and start writing queries.
• Secure by default - Every internal service is bound to loopback. An nginx reverse proxy fronts the console with a login prompt, and a per-instance engine key ensures nothing reaches the engine unauthenticated. No default password exists; credentials are generated uniquely on first boot.
• Production-grade streaming semantics - Event-time watermarks, tumbling, hopping and sliding windows, streaming joins, stateful aggregation, user-defined functions, and exactly-once processing backed by periodic checkpointing.
• Self-contained single node - Embedded metadata database with pipeline state on local disk. No external database to provision.
• Broad connector ecosystem - Built-in sources and sinks for Kafka, Redpanda, Kinesis, Pulsar, MQTT, NATS, WebSockets, server-sent events, Delta Lake, Iceberg, and filesystem or object storage.

## Why This Image Instead of Self-Installing

Standing up Arroyo yourself means fetching and verifying the release, writing a cluster configuration, choosing a metadata store, binding every internal service so it is not exposed, adding an authentication layer Arroyo does not provide on its own, and fronting it all with a reverse proxy. This image resolves every one of those decisions in a single launch.

## Browser-Based Console

Pipelines are authored in a console featuring a SQL editor, live query preview, a visual pipeline graph, and per-operator throughput and checkpoint metrics. You can see exactly what a query is doing before and after you start it.

## Getting Started

1. Launch the instance from the AWS Marketplace listing.

2. SSH in and read the generated administrator credentials from the root-only file.

3. Browse to the instance on port 80 and sign in.

4. Write a SQL query in the console, preview it live, and start it as a pipeline.

5. Connect an external source such as Kafka to stream your own data through it.

## 24/7 cloudimg Support

This image includes around-the-clock technical support by email and chat covering deployment, connecting external sources and sinks, engine sizing, checkpointing and state, user-defined functions, TLS termination, and upgrades. Critical issues receive a one-hour average first response.

Arroyo is distributed under the Apache License 2.0 or the MIT license, at your option. All product and company names are trademarks or registered trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.