ADPtä

ADPtä is a modular software framework for adaptive data processing and analytics, designed to run across cloud, on‑premises, and edge environments. The name combines the acronym ADP with a stylized tä to signal extensibility and a Scandinavian-inspired branding. The framework aims to unify streaming and batch workloads under a single pipeline model, emphasizing adaptability to changing workloads and resource availability.

ADPtä’s architecture centers on a lightweight core runtime, a plugin manager for data sources and processors, a policy engine for scheduling and data governance, and a resilient data transport layer. The system supports stateful processing, fault tolerance, and configurable processing guarantees such as exactly-once or at-least-once semantics. A pluggable scheduler uses resource metrics and data locality to place tasks where they will perform best, including multi‑cloud and edge deployments.

Key features include modular connectors for databases, message queues, and file formats; a domain-specific language for building pipelines; policy-based enforcement of security and privacy rules; and observability tools for tracing, metrics, and auditing. ADPtä emphasizes data locality and minimal data movement to meet privacy and latency requirements.

The project provides bindings for Python, Java, and Rust, and supports common formats like JSON, Parquet, and Avro. It integrates with Kubernetes and other container platforms, and can deploy alongside cloud-native services. Development began in the open‑source community around 2022–2023, with ongoing governance by a community council and permissive licensing.

See also: data processing frameworks, stream processing, edge computing.