Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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Updated
Jul 16, 2024 - Python
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
🚀 The Mixin TEE-BFT-DAG network reference implementation.
A distributed, fault-tolerant task queue
Go Implementation of the Spacemesh protocol full node. 💾⏰💪
Workflow Engine for Kubernetes
A scalable inference server for models optimized with OpenVINO™
Setheum: The Unified Web3 Base Layer - Scalably Solving Web3’s Fragmentation Problems. Ready for hacking 🚀
Iris is an extensible asynchronous header-only framework written in pure modern C++, including a M:N task scheduler (with coroutine support for C++ 20 optionally) and an advanced DAG-based task dispatcher.
A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.
Dag server based on quartz, allows to execute batch processes modeled as DAG (Direct Acyclic graph). Inspired by Apache Airflow and IBM Datastage
Lightweight function pipeline (DAG) creation in pure Python for scientific workflows 🕸️🧪
Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.
Hathor core is the official and reference client for operating a full node in Hathor Network.
A high performance Python graph library implemented in Rust.
Taier is a big data development platform for submission, scheduling, operation and maintenance, and indicator information display
A library enabling DAG structuring of data processing programs such as ETLs
View the DAG and all public transactions https://explorer.obyte.org
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