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Databases are hard. Making the right choices early and keeping things running smoothly even when budget pressures and customer requests start piling on — that's the hard part that many solopreneurs and indie founders struggle with.
I certainly do.
So here's a journey through my learnings and experiences from running SaaS offerings with sizeable —talking about terabytes of data— databases.
The blog post: https://thebootstrappedfounder.com/indie-hacking-databases-at-scale/ The podcast episode: https://tbf.fm/episodes/374-indie-hacking-databases-at-scale
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Here are a few tools I use. Using my affiliate links will support my work at no additional cost to you.- Notion (which I use to organize, write, coordinate, and archive my podcast + newsletter): https://affiliate.notion.so/465mv1536drx- Riverside.fm (that's what I recorded this episode with): https://riverside.fm/?via=arvid- TweetHunter (for speedy scheduling and writing Tweets): http://tweethunter.io/?via=arvid- HypeFury (for massive Twitter analytics and scheduling): https://hypefury.com/?via=arvid60- AudioPen (for taking voice notes and getting amazing summaries): https://audiopen.ai/?aff=PXErZ- Descript (for word-based video editing, subtitles, and clips): https://www.descript.com/?lmref=3cf39Q- ConvertKit (for email lists, newsletters, even finding sponsors): https://convertkit.com?lmref=bN9CZw
Arvid shares his journey of scaling Podscan's database from a simple setup to managing millions of podcasts, episodes, and daily data tracking. He highlights the challenges of handling such large volumes of data as a solo founder, emphasizing the importance of not letting database management consume all his time.
A critical lesson learned was the significance of database indices. Arvid discusses how he faced severe performance issues as queries began taking longer. He emphasizes the necessity of setting up indices early during table creation and how introducing them later can pose immense challenges.
Arvid introduces the concept of AWS RDS's blue-green deployments, a game-changer for managing databases while maintaining uptime. By creating a copy of the database, he could perform maintenance tasks without affecting the primary database’s ability to serve requests.
Arvid explains the complexities involved in database storage and optimization, recounting his attempts to reclaim space after deleting old transcripts. He successfully reduced his database size but had to utilize blue-green deployments to optimize it without downtime.
The podcast discusses the intricacies of implementing full-text search within a massive database and the synchronization of a self-hosted search engine. This introduced additional engineering challenges to keep the search engine aligned with the primary database.
Arvid offers practical insights for indie hackers beginning their database journey. He recommends starting with a managed database service, keeping implementations generic, and planning for future scaling without over-engineering from the start.
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