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Based on our record, Apache Airflow should be more popular than Cadence Workflow. It has been mentiond 75 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Is this really true? Something that can be supported by clear evidence? I’ve seen this trotted out many times, but it seems like there are interesting Apache projects: https://airflow.apache.org/ https://iceberg.apache.org/ https://kafka.apache.org/ https://superset.apache.org/. - Source: Hacker News / 2 months ago
Apache Airflow offers simplicity when it comes to scheduling, authoring, and monitoring ML workflows using Python. The tool's greatest advantage is its compatibility with any system or process you are running. This also eliminates manual intervention and increases team productivity, which aligns with the principles of Platform Engineering tools. - Source: dev.to / 3 months ago
Data orchestration tools are key for managing data pipelines in modern workflows. When it comes to tools, Apache Airflow, Dagster, and Flyte are popular tools serving this need, but they serve different purposes and follow different philosophies. Choosing the right tool for your requirements is essential for scalability and efficiency. In this blog, I will compare Apache Airflow, Dagster, and Flyte, exploring... - Source: dev.to / 4 months ago
Data pipelines: Apache Kafka and Airflow are often used for building data pipelines that can continuously feed data to models in production. - Source: dev.to / 4 months ago
This article demonstrates how to work with near real-time and historical data using the dlt package. Whether you need to scale data access across the enterprise or provide historical data for post-event analysis, you can use the same framework to provide customer data. In a future article, I'll demonstrate how to use dlt with a workflow orchestrator such as Apache Airflow or Dagster.``. - Source: dev.to / 6 months ago
Uber (in Denmark) | https://www.uber.com/ | Software Engineer (all levels) | Hybrid EU (Aarhus, Denmark) | Full-time | https://www.uber.com/dk/en/careers/list/?location=DNK--Aarhus We're an office of 120+ people, all in engineering, we're responsible for creating and supporting Uber's compute platforms for the entire company. Come join us in Aarhus as we continue to build and scale out our platform of: - One of... - Source: Hacker News / 8 months ago
Emit events from your primary DB (postgres, etc.) to something like kafka or rabbitmq and then catch that in your search engine. There's also some end-to-end solutions like temporal (temporal.io) or cadence (https://cadenceworkflow.io/). Source: over 2 years ago
You should definitely check Uber Cadence https://cadenceworkflow.io/. Source: almost 3 years ago
Cadence: https://cadenceworkflow.io. - Source: Hacker News / almost 3 years ago
Dear community, I will be please to get your feedback to choose a schedule engine in 2022 in microservice context. On this field they are at least 2 challengers to me, ¹ nomad from hashicorp and ² cadence from uber. While kubernetes lead this field. Source: over 3 years ago
Make.com - Tool for workflow automation (Former Integromat)
Camunda - The Universal Process Orchestrator
ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.
Workflow Engine - .NET & .NET Core workflow engine, and a standalone workflow server that enable you to add custom executable workflows of any complexity to your app.
Microsoft Power Automate - Microsoft Power Automate is an automation platform that integrates DPA, RPA, and process mining. It lets you automate your organization at scale using low-code and AI.
Activiti - Activiti is a light-weight workflow and Business Process Management (BPM) Platform targeted at...