Going From Transactional To Analytical And Self-managed To Cloud On One Database With MariaDB
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Summary The database market has seen unprecedented activity in recent years, with new options addressing a variety of needs being introduced on a nearly constant basis. Despite that, there are a handful of databases that continue to be adopted due to their proven reliability and robust features. MariaDB is one of those default options that has continued to grow and innovate while offering a familiar and stable experience. In this episode field CTO Manjot Singh shares his experiences as an early user of MySQL and MariaDB and explains how the suite of products being built on top of the open source foundation address the growing needs for advanced storage and analytical capabilities. 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. With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Go to dataengineeringpodcast.com/linode today and get a $100 credit to launch a database, create a Kubernetes cluster, or take advantage of all of their other services. And don’t forget to thank them for their continued support of this show! You wake up to a Slack message from your CEO, who’s upset because the company’s revenue dashboard is broken. You’re told to fix it before this morning’s board meeting, which is just minutes away. Enter Metaplane, the industry’s only self-serve data observability tool. In just a few clicks, you identify the issue’s root cause, conduct an impact analysis—and save the day. 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Sign up free… or just get the free t-shirt for being a listener of the Data Engineering Podcast at dataengineeringpodcast.com/rudder. Data teams are increasingly under pressure to deliver. According to a recent survey by Ascend.io, 95% in fact reported being at or over capacity. With 72% of data experts reporting demands on their team going up faster than they can hire, it’s no surprise they are increasingly turning to automation. In fact, while only 3.5% report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. 85%!!! That’s where our friends at Ascend.io come in. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java. Ascend automates workloads on Snowflake, Databricks, BigQuery, and open source Spark, and can be deployed in AWS, Azure, or GCP. Go to dataengineeringpodcast.com/ascend and sign up for a free trial. If you’re a data engineering podcast listener, you get credits worth $5,000 when you become a customer. Your host is Tobias Macey and today I’m interviewing Manjot Singh about MariaDB, one of the leading open source database engines Interview Introduction How did you get involved in the area of data management? Can you describe what MariaDB is and the story behind it? MariaDB started as a fork of the MySQL engine, what are the notable differences that have evolved between the two projects? How have the MariaDB team worked to maintain compatibility for users who want to switch from MySQL? What are the unique capabilities that MariaDB offers? Beyond the core open source project you have built a suite of commercial extensions. What are the use cases/capabilities that you are targeting with those products? How do you balance the time and effort invested in the open source engine against the commercial projects to ensure that the overall effort is sustainable? What are your guidelines for what features and capabilities are released in the community edition and which are more suited to the commercial products? For your managed cloud service, what are the differentiating factors for that versus the database services provided by the major cloud platforms? What do you see as the future of the database market and how we interact and integrate with them? What are the most interesting, innovative, or unexpected ways that you have seen MariaDB used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on MariaDB? When is MariaDB the wrong choice? What do you have planned for the future of MariaDB? Contact Info LinkedIn @ManjotSingh on Twitter 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 shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning. 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 hosts@dataengineeringpodcast.com) with your story. To help other people find the show please leave a review on Apple Podcasts and tell your friends and co-workers Links MariaDB HTML Goodies MySQL PHP MySQL/MariaDB Pluggable Storage InnoDB MyISAM Aria Storage SQL/PSM MyRocks MariaDB XPand BSL == Business Source License Paxos MariaDB MongoDB Compatibility Vertica MariaDB Spider Storage Engine IHME == Institute for Health Metrics and Evaluation Rundeck MaxScale The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Support Data Engineering Podcast
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