AI · May 9, 2026
Dagzer
🦀 High-Performance Orchestration | 1M+ Executions/Sec.
Dagzer launched on May 9, 2026 with 1 votes.
What it does
At Dagzer, we built a next-generation distributed orchestration engine, ensuring infrastructure is never a bottleneck. Executing 1M tasks per second with sub-millisecond latency, our platform provides a robust foundation for enterprise systems. Crafted from Rust using Hexagonal Architecture, we simplify advanced workflow automation, letting teams safely connect distributed services. From agentic AI loops to high-volume pipelines, Dagzer is the ultimate AI-ready infrastructure to scale endlessly.
Build, deploy, and scale intelligent workflows with AI agents, automation, and orchestration — all in one enterprise-grade platform. Alternative to Zapier, Make, and n8n.
Does a similar job
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Octopus – a directed acyclic graph for app development2023 · github.com · ▲84Directed acyclic graphs are muched discussed in comp-sci, but octopus appears to be the first reusable, turnkey, ready-to-wear, off-the-shelf implementation of a DAG for application development, in any language, that I'm aware of. This is remarkable because DAGs hit a sweet spot in the middle of the three common programming paradigms (OO, event-driven, functional). Let's have a DAG as the top-level structure of our applications. Data-fetching and onChange handlers live in DAG nodes, next to the data they act on. The UI flows out from the DAG with fine-grained reactivity. Our app state is…
DAGForgeNov 2025 · dagforge.com · ▲8Built DAGForge to make generating and validating Airflow DAGs much faster. Most AI tools produce broken or incomplete DAGs, so I added: Airflow-aware validation (operators, imports, params) Syntax + security checks Deterministic JSON parsing to avoid hallucinations Support for local or cloud LLMs Would love feedback from data engineers and Airflow users. Demo: https://dagforge.com
Apache Airflow on Astronomer2018 · astronomer.io · ▲87Write and deploy custom ETL pipelines in Python
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