Leveling Up Open Source Data Integration With Meltano Hub And The Singer SDK
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Summary Data integration in the form of extract and load is the critical first step of every data project. There are a large number of commercial and open source projects that offer that capability but it is still far from being a solved problem. One of the most promising community efforts is that of the Singer ecosystem, but it has been plagued by inconsistent quality and design of plugins. In this episode the members of the Meltano project share the work they are doing to improve the discovery, quality, and capabilities of Singer taps and targets. They explain their work on the Meltano Hub and the Singer SDK and their long term goals for the Singer community. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. 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If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription Your host is Tobias Macey and today I’m interviewing Douwe Maan, Taylor Murphy, and AJ Steers about their work to level up the Singer ecosystem through projects like Meltano Hub and the Singer SDK Interview Introduction How did you get involved in the area of data management? Can you start by describing what the Singer ecosystem is? What are the current weak points/challenges in the ecosystem? What is the current role of the Meltano project/community within the ecosystem? What are the projects and activities related to Singer that you are focused on? What are the main goals of the Meltano Hub? What criteria are you using to determine which projects to include in the hub? Why is the number of targets so small? What additional functionality do you have planned for the hub? What functionality does the SDK provide? How does the presence of the SDK make it easier to write taps/targets? What do you believe the long-term impacts of the SDK on the overall availability and quality of plugins will be? Now that you have spun out your own business and raised funding, how does that influence the priorities and focus of your work? How do you hope to productize what you have built at Meltano? What are the most interesting, innovative, or unexpected ways that you have seen Meltano and Singer plugins used? What are the most interesting, unexpected, or challenging lessons that you have learned while working with the Singer community and the Meltano project? When is Singer/Meltano the wrong choice? What do you have planned for the future of Meltano, Meltano Hub, and the Singer SDK? Contact Info Douwe Website Taylor LinkedIn @tayloramurphy on Twitter Blog AJ LinkedIn @aaronsteers on Twitter aaronsteers on GitLab Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don’t forget to check out our other show, Podcast.__init__ to learn about the Python language, its community, and the innovative ways it is being used. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story. To help other people find the show please leave a review on iTunes and tell your friends and co-workers Join the community in the new Zulip chat workspace at dataengineeringpodcast.com/chat Links Singer Meltano Podcast Episode Meltano Hub Singer SDK Concert Genetics GitLab Snowflake dbt Podcast Episode Microsoft SQL Server Airflow Podcast Episode Dagster Podcast Episode Podcast.__init__ Episode Prefect Podcast Episode AWS Athena Reverse ETL REST (REpresentational State Transfer) GraphQL Meltano Interpretation of Singer Specification Vision for the Future of Meltano blog post Coalesce Conference Running Your Data Team Like A Product Team The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Support Data Engineering Podcast