Flyte vs Metaflow
Flyte
flyte.orgMetaflow
metaflow.orgSide by side
| Figure | Flyte | Metaflow |
|---|---|---|
| Price from | $950/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | Yes | Yes |
| Web | Yes | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 5 | 1 |
| Spec score · MLOps Platforms | 9.1 (#1) | 8.6 (#4) |
| Spec score · DataOps Platforms | 9.0 (#4) | 8.4 (#7) |
| Deployment | Flyte 2 can run locally with a devbox or on a user's cluster; the site provides `pip install flyte` and `flyte start devbox` setup commands. | Workflows can be deployed to production with one command and can react to events. |
| Integrations | The Flyte site lists integrations including Apache Spark, Ray, PyTorch Elastic, BigQuery, Snowflake, Weights & Biases, OpenAI Agents SDK, LangGraph, CrewAI, Pydantic AI, MLflow, Dask, and Databricks. | Documented integrations include AWS Batch, AWS Step Functions, Kubernetes, Argo Workflows, and Apache Airflow. |
| Origin | Flyte was built internally at Lyft in 2016, open-sourced in 2020, and joined the Linux Foundation AI & Data in 2022. | Metaflow was originally developed at Netflix and was open-sourced in 2019. |
| Public API | Flyte services expose gRPC APIs and publish an OpenAPI schema accessible from the local API endpoint. | The API reference documents Client, FlowSpec, Runner, Deployer, Current, S3, Cards, ArgoEvent and flow and step decorators. |
| Rating on G2 | 4.7 out of 5 from 11 reviews, but the G2 listing describes Flyteai.com sales-coaching software rather than Flyte OSS. | 4.5 out of 5 from 3 reviews |
| Self-hosting | Flyte OSS documentation says users deploy and manage the platform on their own cloud infrastructure. | Scaling and production features require deployment into the customer’s cloud account or Kubernetes cluster using infrastructure templates. |
| Support | The Team plan lists one business day Sev 1 support, while Enterprise lists custom white-glove support. | The documentation points users to the Metaflow Slack community for help. |
| What it does | Flyte is an open-source runtime for orchestrating AI workloads such as training, serving and agent workflows, with automatic recovery from failures. | Metaflow is a Python library for developing, deploying and operating data-intensive data-science, machine-learning and AI applications. |
Plans
Flyte
- Flyte OSSFree
- Flyte OSSFree
- Team$950 a month
- Union.ai Team (enterprise Flyte platform)$950 a month
- EnterprisePriced on request
In their own words
Flyte
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.
Metaflow
Metaflow is a free, open-source Python library for developing, deploying, and operating data-intensive data science, machine learning, and AI applications. It automatically tracks flows, experiments, and artifacts, and supports local workflow construction and testing. For larger workloads, it can use compute in a customer’s cloud account or Kubernetes clusters. Documented integrations include AWS Batch, AWS Step Functions, Kubernetes, Argo Workflows, and Apache Airflow. Deployments can use AWS, Azure, Google Cloud, Kubernetes, or on-premises clusters; artifact storage options include AWS S3, Azure Blob Storage, and Google Cloud Storage. The Python package runs on macOS and Linux, while Metaflow Sandbox offers free browser access to cloud and Kubernetes stacks. The project is licensed under Apache License 2.0, and its own-cloud model can use existing infrastructure and security policies. A local-only setup does not support external compute scaling or production-grade deployments. Metaflow is aimed at data scientists and ML or AI engineers; its documentation says it offers little benefit for small notebook experiments without scaling, criticality, or complexity needs.