An open-source IoT platform for data management and processing, built in Elixir with Cassandra/ScyllaDB and RabbitMQ.
Astarte is an open-source IoT platform focused on data management and processing for connected device fleets. It provides data modeling, automated data reduction, real-time events, and a full suite of features expected in a modern IoT platform. It solves the challenge of reliably ingesting, processing, and managing data from large numbers of IoT devices.
IoT developers and organizations building scalable IoT solutions that require robust data ingestion, processing, and device management capabilities.
Developers choose Astarte for its turnkey approach, combining data modeling, real-time processing, and automated reduction in a single platform. Its Kubernetes-native design and use of battle-tested technologies like Elixir, Cassandra, and RabbitMQ ensure scalability and reliability for production IoT deployments.
Core Astarte Repository
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Astarte bundles data modeling, automated reduction, and real-time events into a single platform, eliminating the need to assemble multiple services from scratch.
Built on Elixir for concurrency and Cassandra/ScyllaDB for storage, it ensures high performance and fault tolerance for large device fleets, as highlighted in the README.
With a dedicated Kubernetes operator and astartectl tool, deploying and managing production clusters is streamlined, making it cloud-ready.
Official SDKs for Python, Qt5, ESP32, and Elixir simplify device integration, reducing development time for various hardware types.
The README explicitly warns that moving to production is 'tricky' and requires deep knowledge of the platform's architecture, which can slow initial rollout.
The demo uses ScyllaDB under the Business Source License (BSL), potentially requiring a commercial license for production use over certain thresholds, adding cost and legal overhead.
Astarte is designed as a first-class citizen on Kubernetes, making it less suitable for environments without container orchestration or those preferring simpler deployments.