Orchestrate Meltano Jobs with Dagster

Meltano is an open-source tool that aims to solve the problem of ELt (Extract, Load, Transform) in the new world of SaaS. It provides a simple premise: writing any data extraction program to pull data from a source and writing any data loading program to push your data into a destination. Meltano was built on top of the Singer specification and has added an SDK for building new integrations, a configuration wrapper, and an integrations hub to support the community of Singer users. It offers over 550 integrations and is being prepped for its cloud service launch. The author of this blog post used Meltano to ingest data from GitHub and store it in a Dockerized Postgres database. They then added this pipeline to Dagster, an open-source orchestration platform, using the dagster-meltano library. This integration allows users to execute Meltano commands from within Dagster, enabling features like scheduling, dependency management, end-to-end testing, partitioning, and more. The author demonstrated three ways to run Meltano from Dagster: importing jobs from Meltano projects, issuing a meltano_run_op() command, and using the meltano_command_op() function to make other configuration changes programmatically. The guide aims to help anyone looking to tap into Meltano's capabilities as part of a Dagster managed project.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.