Key Differences Between Prefect Server and Prefect Cloud: Workers use these definitions to submit individual flow runs to the designated infrastructure, allowing for dynamic resource allocation and scalability. This approach requires setting up a work pool and a base job template. This process manages all runs for the associated deployments, providing a persistent environment for flow execution. In this model, similar to deploying a webserver, users author their workflows and maintain a long-running process, often within a Docker container. Here's an in-depth look at these models: Long-Running Process Model Prefect's server models for orchestrating flows offer two primary deployment approaches, each catering to different levels of control over the execution infrastructure. Both tools have their strengths and dedicated communities, making them solid choices for workflow orchestration. In conclusion, the choice between Prefect and Airflow often comes down to specific use cases, preferences for ease of use versus control, and the desired level of infrastructure management. Airflow's extensive plugin system allows users to extend its capabilities, though this can sometimes lead to dependency management issues.Prefect provides a unified API for both cloud and on-premises solutions, making it easier to switch or combine the two.Airflow's managed services, such as Astronomer and Google Cloud Composer, provide similar features but may come at a higher cost.Prefect Cloud offers additional features like automations, RBAC, SSO, and audit logs, which are not all available in the open-source version.Prefect's hybrid execution model allows for scaling without the need for complex infrastructure setups.Airflow is known to scale well, but it might require more infrastructure management.Airflow, being an older and more established project, has a larger user base and a wealth of community-contributed plugins and integrations.Prefect's community is known for being highly responsive and supportive. Both Prefect and Airflow have active communities.Airflow requires users to define workflows as Directed Acyclic Graphs (DAGs), which can be less intuitive for those not familiar with this paradigm.Prefect's philosophy of 'code as workflows' means users don't have to adapt their code to fit the orchestrator instead, the orchestrator adapts to the user's code.Prefect is designed to be more opinionated with sensible defaults, which can reduce the need for extensive configuration.Airflow offers extensive customizability, which can be a double-edged sword it allows deep control but can increase complexity.Airflow's UI has improved over time, but some users find its initial setup and configuration more complex.Prefect's intuitive API and UI are frequently praised for their simplicity and ease of use.Here's an in-depth look at the insights gathered from various sources, including Prefect vs Airflow Reddit discussions and official documentation. Celery would fit nicely as another execution backend.When comparing Prefect and Airflow, the community often highlights several key differences and preferences. Currently, Prefect ships with local, multiprocessing, threaded, and Dask distributed backends, and there’s an outstanding PR for a redis-queue backend. If all of that workflow logic “passes”, Prefect then runs your task on whatever backend you prefer, which is where Celery could come in to play. Prefect’s primary job is to supply workflow semantics around your functions - things like what to do if they fail, how to handle logging, retries, conditional logic, responding to upstream results, complex dependencies, scheduling, etc. Prefect, in contrast, is a workflow management system. Dask isn’t exactly the same but similar enough for the purpose of this conversation. So Celery’s primary job is to take a function and run it. A “broker” submits work to a pool of workers, who run the task/job/function and indicate that they’ve finished. Celery is a system for executing work, usually in a distributed fashion. Jeremiah: Hi, it’s a good question - many technologies can be used together, and in fact it would be straightforward to run Prefect on top of a Celery backend (though we prefer Dask for the same purpose). I think the differences from Airflow are well described in the docs, yet quite clear, but I'm not sure why I should prefer it over Celery. Archived from the Prefect Public Slack Communityįrassetto.stefano: This will probably sounds like a weird question, but how is Prefect different from Celery?.
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