![]() ![]() You can build data pipelines and workflows with over 250+ pre-built components that perform tasks with a couple clicks.Empowering everyone from domain experts with zero programming knowledge to technically proficient data engineers to do their best jobs. This orchestration platform offers no-code, full-code (Python, SQL, dbt orchestrator …), and API orchestrations.From orchestrating workflows to building ETL data pipelines, or even launching machine learning products, Keboola offers plenty of out-of-the-box features to streamline your business processes. Keboola helps you manage, optimize, and automate all your data operations in one platform. This data platform as a service offers you process automation for every step of the data lifecycle. While we might be biased, customer reviews (4,7 out of 5 stars on G2) support our claims. Keboola is the best alternative to Airflow (and other workflow engines). Let’s take a look at the best Apache Airflow alternatives on the market today. Luckily, alternative tools make your life easier. What’s worse, tasks are scheduled via the execution_date parameter, which is interpreted not as the start time for a DAG, but as the end of an interval capped by the DAG’s start time. You have to create two identical tasks to mimic job repetition. All tasks need to be run via a date scheduler, but the date scheduler prevents triggering the same task twice at the same time. As a design choice, Airflow limits users in how they trigger tasks. On Windows, your only option is to run Airflow with docker-compose. What’s worse, Airflow doesn’t preserve metadata for deleted jobs, so debugging and data management are especially challenging. ![]() There is no way to redeploy a deleted Task or DAG. Apache Airflow’s workflow as code philosophy excludes domain experts who need to self-serve their data needs without knowing Python or another programming language. ![]()
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