With over 16,500 GitHub stars and a track record powering connected vehicle fleets, smart city sensor networks, and industrial IoT deployments, EMQX is the MQTT messaging platform engineered to handle 100 million concurrent device connections in a single cluster while processing millions of messages per second with sub-millisecond latency. The protocol stack supports MQTT 5.0, 3.1.1, and 3.1 with full QoS 0/1/2 support, shared subscriptions, retained messages, and will messages, plus MQTT over QUIC for faster connection setup, reduced head-of-line blocking, and seamless connection migration on mobile networks. The gateway framework extends connectivity to MQTT-SN, CoAP, LwM2M, STOMP, and ExProto for bridging legacy industrial protocols. The SQL-based rule engine processes and transforms messages in real time with over 50 pre-built integrations including Kafka, PostgreSQL, MySQL, MongoDB, InfluxDB, TimescaleDB, ClickHouse, Redis, AWS Kinesis, GCP Pub/Sub, and Azure Event Hubs. The visual Flow Designer creates data processing pipelines without code. Built on Erlang/OTP with a masterless distributed architecture using Mria for state replication, the cluster separates Core nodes for data consistency and Replicant nodes for client-handling workloads. Authentication supports username/password, JWT, PSK, X.509 certificates, and LDAP with configurable ACL rules. The built-in dashboard provides real-time monitoring of connections, subscriptions, topics, message rates, and cluster health. Deployment runs via Docker, Kubernetes with the EMQX Operator, or native packages. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSL 1.1 licensed.

Thousands of devices speaking four different protocols is where IoT projects usually dissolve into glue code; Magistrala replaces that tangle with one platform where MQTT, HTTP, WebSocket, and CoAP clients share a single identity, provisioning, and messaging model. You organise work into domains, register clients for devices and applications, and connect them to channels that control who publishes and who subscribes, with fine-grained policies deciding which client may touch which channel. Protocol adapters bridge the transports, so a sensor publishing over MQTT and a dashboard reading over WebSocket meet in the same channel without translators in between. Telemetry lands in TimescaleDB through dedicated writer services and comes back out through reader APIs, while the bundled three-node FluxMQ cluster carries the messaging load with mutual TLS on device connections. The rules engine reacts to incoming messages with conditions and actions, alarms flag the readings that breach them, and reports package fleet data for the people who never open a terminal. A Community web UI covers domains, clients, channels, messages, and rules for day-to-day operation, and everything deploys as one Docker Compose stack with Prometheus metrics and Jaeger tracing already wired in. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

On the factory floor, the data already exists; it is just locked inside machines, PLCs, and protocols nobody on the analytics team speaks. StreamPipes unlocks it with guided adapters for OPC UA (including a web-based node browser), MQTT, Kafka, Pulsar, REST services, and industrial controllers, turning each source into a live stream in minutes. Domain experts then drag those streams into the pipeline editor, chain processors and sinks on a canvas, and watch connection validation check schema compatibility as they build, with live preview showing real values before anything is saved. Pipelines filter, enrich, aggregate, and route machine data, raise alerts, and write results to the built-in time-series data lake, where the data explorer charts history and spots trends. Finished pipelines run under an overview that starts, stops, and bulk-manages them, while detail views expose logs, metrics, status, and the pipeline as code. Live dashboards carry the same data to shop-floor screens and operations centers, organized around assets so a line, a cell, or a single machine becomes the navigation unit. Developers extend everything with custom adapters, processors, and sinks built on the Java SDK and deployed as microservices, or drive the platform from Python, Go, and Java clients. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Every physical device on your network gets a living digital counterpart in Eclipse Ditto: a Thing whose Features hold its current state, desired state, and properties, readable and writable through APIs even while the device itself is offline. Your application talks to the twin over a REST-like HTTP API for CRUD and search, over WebSocket for real-time bidirectional streams, or over Server-Sent Events for change notifications, and Ditto routes commands down the live channel to the actual device when it is connected. Devices and backends connect through managed Connections to MQTT, AMQP 1.0 and 0.9.1, Apache Kafka, and HTTP endpoints, with payload mapping that translates between device formats and Ditto Protocol JSON. Fine-grained Policies decide per subject and resource who may read a temperature, change a setpoint, or receive an event, including namespace-scoped entries and partial change notifications that only reveal fields a subscriber may see. Search across millions of twins uses an RQL query language with custom MongoDB indexes, and Web of Things integration generates Thing Descriptions scoped to each requester's permissions. The bundled Explorer UI lets operators browse Things, inspect Features, and time-travel a twin's state to any past revision or timestamp to see exactly what changed and when. OpenID Connect and basic authentication protect the gateway, and Prometheus metrics expose live entity counts per namespace. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. EPL-2.0 licensed.

OpenRemote is an IoT platform that models every building, EV charger, solar panel, and street light as an asset in one tree, then maps, charts, and automates them from a single web dashboard. Define your own asset types, and give each attribute live readings, writable setpoints, history, and forecasts. Connect hardware with protocol agents for HTTP, MQTT, Modbus, KNX, Z-Wave, LoRaWAN, SNMP, and serial, discovering devices or importing project files where the protocol allows. Plot assets on a map with live position and heading, tint markers by attribute value, and add geofences and GeoJSON layers. Automate with When-Then rules, a drag-and-drop Flow editor, or Groovy and JavaScript rules, and run them on a schedule. Raise e-mails, push notifications, webhooks, or assignable alarms from the result. Compose shareable dashboards in Insights from nine widget types, including charts, KPIs, gauges, maps, and tables. Give each customer a realm with its own users, roles, and white-label branding. Sync edge gateways to a central instance and open them remotely through tunnels. Let devices with X.509 certificates register themselves. Read and write every attribute over REST, MQTT, or WebSocket, and let AI assistants manage assets in plain language through the MCP server. Typical projects span smart cities, building and energy management, and equipment fleets, in an interface that speaks nine languages. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

A single ejabberd node carries chat, device telemetry, voice calls, and federated messaging at once, because the same Erlang server speaks XMPP, MQTT, SIP, and Matrix over one authentication, storage, and clustering layer. Users get standards-based instant messaging with group chats, message archives, publish-subscribe, message carbons, push notifications, and OMEMO encryption, and your server federates with the global XMPP network out of the box. Devices publish and subscribe through the built-in MQTT broker on TCP or WebSocket transports, sharing accounts and access rules with your chat users instead of needing a second broker. Voice and video calls route through the integrated SIP gateway and STUN/TURN support, so WebRTC clients get signalling and media relay from the same deployment. Matrix support bridges federated rooms into the same infrastructure, letting two decentralised ecosystems interoperate without a separate bridge stack to babysit. Clustering with consistent hashing scales a deployment across nodes, and a single node is rated at two million concurrent sessions for very large communities. Operators manage everything from the web admin and command line, with SQL or Mnesia storage, LDAP authentication, and virtual hosting for multiple domains on one server. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPL-2.0 licensed.

Zigbee2MQTT bridges a Zigbee smart home network to MQTT so bulbs, switches, sensors, and locks from hundreds of vendors work with your own automation server instead of each manufacturer's cloud bridge. It supports 5,798 devices from 608 vendors, so a Philips Hue bulb, an IKEA TRÅDFRI switch, an Aqara sensor, and a Tuya plug can all join one coordinator and speak one protocol. The built-in frontend on port 8080 shows every paired device with its link quality, battery level, and live state, and lets you rename, reconfigure, bind, or remove devices without editing YAML. A network map view charts which routers carry traffic for which end devices, making weak spots and dead zones visible before automations start failing. Groups collect devices that should act together, scenes capture lighting states for a room, and bindings let a switch talk directly to a bulb even when the server is briefly offline. Firmware stays current through over the air updates you can trigger or schedule per device from MQTT topics or the frontend, including downgrades when a new release misbehaves. Home Assistant picks everything up automatically through MQTT discovery, while openHAB, Domoticz, and Node-RED flows subscribe to the same plain JSON topics. The coordinator plugs into the host by USB or joins over the local network, while the bridge, frontend, and broker traffic run headlessly beside Mosquitto or EMQX. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPL-3.0 licensed.

Wire nodes together in a browser, deploy in one click, and real-time data flows from sources through transformations to outputs: Node-RED is the OpenJS Foundation's flow-based programming tool for event-driven applications. Born at IBM as a proof-of-concept for manipulating MQTT topic mappings, it has become the lingua franca of IoT and automation glue - home automation, industrial control, edge data collection - with a community library of over 5,000 contributed nodes and flows covering protocols, devices, and services. Where visual wiring runs out, JavaScript function nodes written in a rich in-editor code editor take over, and every flow serializes to importable, exportable JSON that shares cleanly and version-controls sensibly. Version 5.0 (2026) delivered the largest editor overhaul in the project's history: a rethought layout with Explorer and Information panels in a split sidebar, a native dark theme with theme variants, improved accessibility, and refreshed node appearance. The runtime is lightweight Node.js, exploiting the event-driven non-blocking model so the same flows run on a Raspberry Pi at the network edge or a cloud VM. Apache-2.0 licensed with 240+ contributors, it pairs naturally with dashboard nodes for live charts and controls.

With over 31,600 GitHub stars and thousands of production deployments, InfluxDB 3 Core is the open-source time series database rebuilt in Rust on the FDAP stack — Apache Flight for high-throughput data transfer, DataFusion for vectorized SQL query execution, Arrow for columnar in-memory representation, and Parquet for compressed columnar storage. The engine delivers sub-10ms query response times on recent data and handles millions of writes per second through line protocol ingestion over HTTP, with unlimited tag cardinality eliminating the high-cardinality limitations that plagued earlier InfluxDB versions. The diskless architecture persists data as compressed Parquet files to S3-compatible object storage, Azure Blob, Google Cloud Storage, or local disk with configurable partitioning strategies, while the write-ahead log and in-memory buffer serve real-time queries against recent data before compaction. Native SQL support through DataFusion includes window functions, CTEs, subqueries, and joins, while InfluxQL maintains backward compatibility with existing InfluxDB 1.x and 2.x applications through the same query API. The embedded Python VM enables processing engine plugins and triggers that execute custom logic on write events, perform cross-database queries, and transform data in real time without external tooling. Flight SQL clients provide high-performance query access from Python, Go, Java, and Rust, and the HTTP API supports writes in line protocol format compatible with Telegraf's 300+ input plugins. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT/Apache 2.0 dual-licensed.

Used by over 80% of Fortune 100 companies including LinkedIn, Netflix, Uber, and Goldman Sachs, Apache Kafka processes trillions of messages per day as the world's most widely deployed distributed event streaming platform. Since version 4.0 released in March 2025, Kafka operates exclusively with KRaft consensus, replacing Apache ZooKeeper entirely with an internal Raft-based metadata quorum managed by controller nodes, reducing operational complexity and eliminating external coordination dependencies. Topics are organized as append-only partitioned commit logs with configurable replication factors across brokers, delivering network-limited throughput with end-to-end latencies as low as 2 milliseconds. Kafka Streams provides a client library for building stateful stream processing applications with exactly-once semantics, windowed aggregations, joins across streams and tables, and interactive queries against local state stores. Kafka Connect integrates with hundreds of systems including PostgreSQL, MySQL, Elasticsearch, Amazon S3, MongoDB, HDFS, and JMS through a standardized connector framework with distributed worker mode and automatic offset management. Share Groups introduced in version 4.2 deliver queue-style consumption semantics alongside traditional consumer groups, enabling Kafka to serve both pub-sub and point-to-point messaging patterns natively. The Schema Registry enforces Avro, Protobuf, and JSON Schema compatibility rules across producers and consumers, preventing schema evolution from breaking downstream applications. Tiered Storage offloads older log segments to object storage like S3 while maintaining transparent consumer access, dramatically reducing local broker storage costs for long-retention topics. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

With 12,400 GitHub stars and adoption across enterprises processing billions of events daily, Redpanda delivers a complete Kafka wire protocol implementation in C++ that existing Kafka producers, consumers, Kafka Connect connectors, and Kafka Streams applications connect to without code changes — eliminating JVM garbage collection pauses and ZooKeeper coordination overhead through a single binary architecture built on the Seastar framework's thread-per-core model. The integrated schema registry supports Avro, Protobuf, and JSON Schema validation directly within the broker without separate infrastructure. Tiered storage automatically offloads cold data to object storage while maintaining seamless consumer access across the full retention window. Redpanda Console provides a web-based management interface for topic inspection, consumer group monitoring, schema management, and ACL configuration. Redpanda Connect extends the platform with 200+ pre-built connectors for data pipelines between databases, cloud services, and streaming systems. Exactly-once semantics with idempotent producers and transactional guarantees ensure data integrity for financial, healthcare, and compliance workloads. The Adaptable Data Plane in version 26.1 enables per-topic performance profiles balancing throughput, latency, and durability within a single cluster. Deploy via Docker or Kubernetes with official Helm charts — a three-node cluster starts with a single rpk command. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSL 1.1 licensed (converts to Apache 2.0 after four years).

When your services need to talk without waiting on each other, Apache RocketMQ carries the conversation: a distributed messaging platform where producers publish to topics and consumers process at their own pace, with delivery guarantees you can build money movement on. Send ordinary messages for fire-and-forget events, transactional messages that commit or roll back with your local database transaction, ordered and FIFO messages for sequences that must not shuffle, and delayed messages that arrive seconds or days later on schedule. Consumers pull with long polling, filter by tag or SQL expression at the broker, and retry failures through built-in retry queues and dead letter queues instead of losing work. Clusters scale by adding brokers, while Controller mode elects broker replicas automatically so a failed node stops being a page. The Proxy component speaks gRPC with modern multi-language clients and adds POP consumption, where messages become invisible while processed and reappear if the consumer never acknowledges. Tiered storage offloads cold messages to cheaper object storage while hot data stays on local disk, and RocketMQ Streams, Connect, and an MQTT bridge extend the same cluster into stream processing, data integration, and device messaging. Lite Mode trims subscription overhead for AI workloads, and the separate RocketMQ Dashboard gives operators a web console for topics, consumers, and message tracing. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Applications publish an event once and stop caring who needs it next: Apache EventMesh receives CloudEvents over plain HTTP, stores them durably, and delivers each one to every subscription that matches. Producers call publish, consumers call subscribe or unsubscribe, and the runtime owns the registry, offsets, acknowledgements, and redelivery that messaging clients usually force you to build yourself. Subscribers choose load-balanced delivery for competing workers, broadcast delivery for every listener, or multicast for selected groups, and they receive events by HTTP long polling, Server-Sent Events, or WebSocket push. Filters drop irrelevant events before they leave the mesh, while transformers reshape payloads so a producer and consumer can disagree about format without either one changing code. Kafka and RocketMQ act as pluggable write-ahead storage, with an in-memory backend for development, and stateless runtime instances scale horizontally without consumer-group rebalancing. Twenty-three connectors move events into and out of RabbitMQ, Pulsar, MongoDB, MySQL change data capture, Redis, S3, Prometheus, Slack, DingTalk, Lark, WeChat, and AI services, each checkpointing offsets so failures replay instead of silently losing data. Agent-to-Agent protocol support and MCP connectors let AI agents exchange asynchronous events alongside synchronous tool calls, and event-triggered agents can publish decisions back into the mesh for downstream delivery. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

With over 9,100 GitHub stars and production deployments powering real-time analytics at companies like SHOPLINE where it reduced API latency by 76.7%, RisingWave is the PostgreSQL-compatible streaming database that collapses the traditional Debezium-plus-Kafka-plus-Flink-plus-serving-database stack into a single Rust-powered system. The platform continuously ingests data from PostgreSQL and MySQL via native CDC connectors that eliminate Debezium middleware, consumes Kafka, Redpanda, Pulsar, and Kinesis topics, accepts webhook events from SaaS applications, and batch-loads historical data from S3 and data warehouses. Standard SQL defines sources, materialized views, and sinks — no new DSL, no Java, and no custom API — while the PostgreSQL wire protocol means psql, DBeaver, pgAdmin, Grafana, Metabase, Superset, Tableau, and every PostgreSQL client library works without modification. Materialized views are incrementally maintained as events arrive, delivering point lookups in single-digit milliseconds without recomputing aggregates from scratch. For long-term retention, RisingWave writes to Apache Iceberg tables with a hosted REST catalog and automated table maintenance including compaction, small-file optimization, and snapshot cleanup, with data queryable by Spark, Trino, DuckDB, and DataFusion. The disaggregated compute-storage architecture uses S3-based state management for elastic scaling, instant failure recovery measured in seconds rather than the minutes-to-hours typical of RocksDB-based systems, and cost-efficient storage tiering. An MCP server enables AI agents to query and operate RisingWave directly. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Kuzzle ships a production-ready backend from day one: data storage with Elasticsearch search, real-time pub/sub notifications, user authentication, role-based permissions, and a multi-protocol API serving HTTP, WebSocket, and MQTT simultaneously on port 7512. Rather than rebuilding these standard features from scratch for each project, you get a ready-made backend that accepts connections from web applications, mobile clients, and IoT devices through one unified API surface. Elasticsearch provides persistent document storage with full-text search, geospatial queries, and aggregation pipelines, while Redis handles internal caching and memory storage operations. The Koncorde real-time engine powers pub/sub messaging and database notifications, enabling clients to subscribe to document changes with filter conditions that trigger instant updates when matching data is created, modified, or deleted. User management includes JWT-based authentication, role-based access control with granular permissions at the controller and action level, and pluggable authentication strategies via Passport.js. The extensible plugin framework allows developing custom business logic, additional authentication providers, storage connectors, and protocol handlers. Client SDKs for JavaScript, Dart, Kotlin, and C++ accelerate frontend development, while the Kourou CLI provides command-line API access and project scaffolding. The Vue.js Admin Console offers a web interface for managing indexes, collections, documents, users, profiles, and roles. Horizontal scaling through masterless cluster mode targets 99.99% uptime without single points of failure. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Logging every drive, charge, and idle stretch of a Tesla to a database you own, TeslaMate shows where the battery went, including degradation, vampire drain, and charging cost. Battery health comes first: the dashboard estimates usable capacity, range lost, and degradation against mileage. Idle losses come next, with Vampire Drain listing how much charge disappears during every idle period and a States view recording every online, asleep, and offline stretch. The car is left alone to fall asleep, so logging adds no extra vampire drain. Charging sessions show curves, energy added and used, efficiency, and cost, using per-location prices attached to geo-fences drawn on a map. Each drive records second-by-second speed, power, elevation, and temperature, plotted on a route map beside tire pressure and consumption charts. Trip, Drives, Efficiency, Drive Stats, Mileage, Updates, Statistics, and a lifetime driving map fill in the rest. Live vehicle data goes out over MQTT to Home Assistant, Node-RED, and Telegram, and old history imports from TeslaFi or tesla-apiscraper. Several vehicles on one Tesla account work together, addresses are looked up automatically, and the web interface offers light, dark, or system themes in 19 languages. Sign-in uses Tesla access and refresh tokens that TeslaMate encrypts with a key you set. It works best on an always-on server. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.