Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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- apache
- apache-airflow
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Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Node-based Visual Programming Toolbox
Apache Beam is a unified programming model for Batch and Streaming data processing.
Ultra-high performance reactive programming
Compositional, streaming I/O library for Scala
👜 Tiny and fast reactive/iterable programming library
Probabilistic data structures for processing continuous, unbounded streams.
🏎️ Streams & Reactive Programming paradigm for Go: declarative and composable API for event-driven applications
Scramjet Platform is a distributed runtime supervisor that can run data processing programs called Sequences and manage local resources on any Linux server, Docker on small edge servers, and even large-scale Kubernetes clusters in the cloud or datacenters without exposing network ports to the public internet.
Go tool + library that publishes GIS vector data to GeoServer via PostGIS — walks a directory of shapefile / GeoJSON / GeoPackage / KML, loads each into PostGIS via GDAL/OGR, then registers the resulting tables as GeoServer feature types. Idempotent. Tested on GeoServer 2.27 LTS + 2.28 stable.
Stream Processing Made Easy
Simple yet powerful live data computation framework.
EtlKit is a lightweight ETL (extract · transform · load) library and data integration toolbox for .NET. Build your own data pipelines programmatically in C# — readable, testable, and tracked in source control like the rest of your code.
Stateful actors on Apache Flink 2.x and Java 21 — durable per-key state, exactly-once messaging, Kafka and Kinesis I/O, Kubernetes-native deployment. Continues the Apache Stateful Functions programming model on the modern Flink line.
Quick integration toolkit for Ixian. Connects apps, IoT devices, AI Agents, and services to the Ixian Platform via REST APIs and message queues (MQTT/RabbitMQ). Provides developers with a simple bridge into secure Ixian communication and Client Discovery.
Json-values allows Java developers to harness the power of persistent data structures when working with JSON data, simplifying complex data manipulation. It provides a purely functional approach to JSON