Flyte vs Mage

Flyte 2 is a durable runtime for AI workloads involving training, serving and agents. Users write workflows as plain Python async functions and use a TaskEnvironment to declare images, resources, secrets and retry policies. Flyte resumes from failed tasks and can recover from out-of-memory kills, preempted nodes and disappearing GPUs. Branches, loops and runtime decisions support dynamic workflows and agents. Native serving integrations include Streamlit, FastAPI, vLLM, SGLang and Ollama, with replicas able to scale to zero when idle. Listed integrations also cover Apache Spark, Ray, PyTorch Elastic, BigQuery, Snowflake, Weights & Biases, OpenAI Agents SDK, LangGraph, CrewAI, Pydantic AI, MLflow, Dask and Databricks. It runs locally with a devbox or on a customer cluster. Union.ai says customer-cloud data planes keep workflow inputs, outputs, logs, code and reports outside its control plane. Flyte is available as free Apache 2.0 open-source software.

Mage is a web platform for building and operating data workflows. Its listed functions include workflow scheduling, pipeline monitoring, data quality checks, and version control. Integrations cover Stripe, Salesforce, BigQuery, HubSpot, databases, SaaS APIs, cloud storage, files, and streams. Hybrid deployment is available. Mage has a free plan, while Starter costs $29 a month, billed monthly, plus $0.50 per CPU-hour. Starter includes one developer seat, one development environment, and 50 AI credits per month. Team costs $100 a month, billed monthly, plus $0.50 per CPU-hour; it supports up to 10 developer seats, includes one environment, and provides 250 shared AI credits per month. Mage is headquartered in Santa Clara, California, United States.