Join database educator Aaron Francis as he gets schooled by database professionals.
Database School
Claim This Podcastby Try Hard Studios
5.0(12 reviews)
30 episodes
Updated Bi-weekly
Accepts GuestsHas SponsorsLocation 🇺🇸
68
Podcast Authority
BetaGoodBased on show quality, social media presence, reviews, charts, and more
Quality78
Social94
YouTube68
Engagement32
Podcast Overview
Join database educator Aaron Francis as he gets schooled by database professionals.
Language
🇺🇲
Publishing Since
6/13/2024
Unlock The Full Podcast Authority Score Report
See how your podcast performs across key metrics
68
Podcast Authority
BetaGoodBased on show quality, social media presence, reviews, charts, and more
Quality78
Social94
YouTube68
Engagement32
8
Excellent Areas
2
Good Performance
9
Growth Opportunities
excellent
Episode Length
1h 10m
Performing excellently!
good
Show Experience
19 episodes over 1.2 years
Recommendations available
Unlock the full report to see detailed tips
needs improvement
Publishing Consistency
Every 23 days
Recommendations available
Unlock the full report to see detailed tips
+16 More Metrics
Unlock comprehensive insights including:
- • YouTube presence analysis
- • Social media reach metrics
- • RSS compliance scoring
- • Podcast 2.0 features
- • Technical standards
What's Included in Your Full Report
Detailed Analytics
- Complete breakdown of all 19 authority metrics
- Personalized recommendations for each metric
- Industry benchmarks and comparisons
- Technical RSS feed analysis and compliance scoring
Growth Strategies
- Step-by-step action plans for improvement
- Quick wins to boost your score immediately
- Pro tips from successful podcasters
Get your free podcast insights report
See how your show performs across every key metric
Instant delivery
No spam
Attract Better Guests
High authority scores make your podcast more attractive to industry leaders and influencers who want to appear on credible shows.
Secure Sponsorships
Sponsors look for podcasts with proven authority and engagement. Your score demonstrates your podcast's value to potential partners.
Grow Your Audience
Understanding your strengths and weaknesses helps you make data-driven decisions to expand your listener base effectively.
3 verified contact emails on file for Database School
Pitch yourself as a guest, propose sponsorships, or reach out directly to the host.
Recent Episodes
January 15, 2026
Infinite, shareable volume storage with Hunter Leath, Archil CEO
<p>Hunter Leath, CEO of Archil, explains how they’re building a “universal storage engine” that sits between your apps and S3—making an S3 bucket behave like a fast, POSIX-compatible disk for containers, servers, and even Lambda. Along the way, we dig into how their SSD-backed clusters and custom protocol avoid the usual small-file pain and where this approach shines (and where it doesn’t).</p><p>Follow Hunter:<br>Twitter/X: https://twitter.com/jhleath<br>Archil Twitter/X: https://twitter.com/archildata<br>Archil: https://archil.com/</p><p>Follow Aaron:<br>Twitter/X: https://twitter.com/aarondfrancis <br>Database School: https://databaseschool.com<br>Database School YouTube Channel: https://www.youtube.com/@UCT3XN4RtcFhmrWl8tf_o49g (Subscribe today)<br>LinkedIn: https://www.linkedin.com/in/aarondfrancis<br>Website: https://aaronfrancis.com - find articles, podcasts, courses, and more.</p><p>Chapters:<br>00:00 - Intro: Archil Data and “S3 as a disk”<br>01:05 - Hunter’s background and the core pitch<br>02:32 - The real problem: state management (S3 vs block storage)<br>05:02 - SQLite on S3: what the stack looks like<br>07:13 - The missing layer: durable SSD-backed clusters<br>10:14 - Who uses this: unstructured data, CI/CD, Git, agents<br>12:15 - Small files + Git performance and avoiding S3 request explosion<br>16:22 - Why they built a new protocol (NFS vs Luster)<br>20:00 - What gets written to S3: real files in your bucket<br>22:29 - S3 limits, throttling, and the “keep it on SSD” escape hatch<br>25:32 - Multi-cloud + R2, and why regions/latency matter<br>32:10 - Pricing model: “pay only when data is active”<br>34:41 - Tradeoffs: random reads and ultra-low-latency metal<br>37:19 - Storage/compute separation and AI/agent-native workflows<br>43:21 - YC timeline + the marketing challenge of a “universal layer”<br>47:34 - Single-tenant clusters for enterprises and why it’s hard<br>50:27 - Where the company is now, hiring, and how to try it (disk.new)</p>
December 18, 2025
Building search for AI systems with Chroma CTO Hammad Bashir
<p>Hammad Bashir, CTO of Chroma, joins the show to break down how modern vector search systems are actually built from local, embedded databases to massively distributed, object-storage-backed architectures. We dig into Chroma’s shared local-to-cloud API, log-structured storage on object stores, hybrid search, and why retrieval-augmented generation (RAG) isn’t going anywhere.</p><p>Follow Hammad:<br>Twitter/X: https://twitter.com/HammadTime<br>LinkedIn: https://www.linkedin.com/in/hbashir<br>Chroma: https://trychroma.com</p><p>Follow Aaron:<br>Twitter/X: https://twitter.com/aarondfrancis <br>Database School: https://databaseschool.com<br>Database School YouTube Channel: https://www.youtube.com/@UCT3XN4RtcFhmrWl8tf_o49g (Subscribe today)<br>LinkedIn: https://www.linkedin.com/in/aarondfrancis<br>Website: https://aaronfrancis.com - find articles, podcasts, courses, and more.</p><p>Chapters:<br>00:00 – Introduction From high-school ASICs to CTO of Chroma<br>01:04 – Hammad’s background and why vector search stuck<br>03:01 – Why Chroma has one API for local and distributed systems<br>05:37 – Local experimentation vs production AI workflows<br>08:03 – What “unprincipled data” means in machine learning<br>10:31 – From computer vision to retrieval for LLMs<br>13:00 – Exploratory data analysis and why looking at data still matters<br>16:38 – Promoting data from local to Chroma Cloud<br>19:26 – Why Chroma is built on object storage<br>20:27 – Write-ahead logs, batching, and durability<br>26:56 – Compaction, inverted indexes, and storage layout<br>29:26 – Strong consistency and reading from the log<br>34:12 – How queries are routed and executed<br>37:00 – Hybrid search: vectors, full-text, and metadata<br>41:03 – Chunking, embeddings, and retrieval boundaries<br>43:22 – Agentic search and letting models drive retrieval<br>45:01 – Is RAG dead? A grounded explanation<br>48:24 – Why context windows don’t replace search<br>56:20 – Context rot and why retrieval reduces confusion<br>01:00:19 – Faster models and the future of search stacks<br>01:02:25 – Who Chroma is for and when it’s a great fit<br>01:04:25 – Hiring, team culture, and where to follow Chroma</p>
December 11, 2025
Scaling DuckDB in the cloud with MotherDuck CEO Jordan Tigani
<p>In this episode of Database School, Aaron Francis sits down with Jordan Tigani, co-founder and CEO of MotherDuck, to break down what DuckDB is, how MotherDuck hosts it in the cloud, and why analytics workloads are shifting toward embedded databases. They dig into Duck Lake, pricing models, scaling strategies, and what it really takes to build a modern cloud data warehouse.</p><p>Follow Jordan:<br>Twitter/X: https://twitter.com/jrdntgn<br>LinkedIn: https://www.linkedin.com/in/jordantigani<br>MotherDuck: https://motherduck.com</p><p>Follow Aaron:<br>Twitter/X: https://twitter.com/aarondfrancis <br>Database School: https://databaseschool.com<br>Database School YouTube Channel: https://www.youtube.com/@UCT3XN4RtcFhmrWl8tf_o49g (Subscribe today)<br>LinkedIn: https://www.linkedin.com/in/aarondfrancis<br>Website: https://aaronfrancis.com - find articles, podcasts, courses, and more.</p><p>Chapters:<br>00:00 - Introduction<br>01:44 - What DuckDB is and why embedded analytics matter<br>04:03 - How MotherDuck hosts DuckDB in the cloud<br>05:18 - Is MotherDuck like the “Turso for DuckDB”?<br>07:38 - Isolated analytics per user and scaling to zero<br>08:51 - The academic origins of DuckDB<br>10:00 - From SingleStore to founding MotherDuck<br>12:28 - Getting fired… and funded 12 days later<br>16:39 - Jordan’s background: Kernel dev, BigQuery, and Product<br>18:36 - Partnering with DuckDB Labs and avoiding a fork<br>20:52 - Why MotherDuck targets startups and the long tail<br>24:22 - Pricing lessons: why $25 was too cheap<br>28:11 - Ducklings, instance sizing, and compute scaling<br>34:16 - How MotherDuck separates compute and storage<br>37:09 - Inside the AWS architecture and differential storage<br>43:12 - Hybrid execution: joining local and cloud data<br>45:14 - Analytics vs warehouses vs operational databases<br>47:41 - Data lakes, Iceberg, and what Duck Lake actually is<br>53:22 - When Duck Lake makes more sense than DuckDB alone<br>56:09 - Who switches to MotherDuck and why<br>58:02 - PG DuckDB and offloading analytics from Postgres<br>1:00:49 - Who should use MotherDuck and why<br>1:03:39 - Hiring plans and where to follow Jordan<br>1:05:01 - Wrap-up</p>
30 total episodes available with 16 transcripts
Recent guests on Database School
Guests from recent episodes — sign up to see every guest that has ever appeared on this show.
Glauber Costa
Guest
Sugu Sougoumarane
Guest
Richard Crowley
Guest
Johannes Schickling
Guest
Josh Howard
Guest
Heikki Linnakangas
Guest
Carl Sverre
Guest
Søren Bramer Schmidt
Guest
Mike Buckbee
Guest
Jesse Hanley
Guest
Monica Sarbu
Guest
Tudor Golubenco
Guest
Deep-dive analytics for Database School
Frequently asked questions
Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email and we'll get back to you as soon as we can.
- What is Database School?
- How often does this podcast release new episodes?
This podcast updates bi-weekly.
- Where can I listen to this podcast?
This podcast is available on 9 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
Yes, this podcast regularly features guests.
Legal Disclaimer
Pod Engine is not affiliated with, endorsed by, or officially connected with any of the podcasts displayed on this platform. We operate independently as a podcast discovery and analytics service.
All podcast artwork, thumbnails, and content displayed on this page are the property of their respective owners and are protected by applicable copyright laws. This includes, but is not limited to, podcast cover art, episode artwork, show descriptions, episode titles, transcripts, audio snippets, and any other content originating from the podcast creators or their licensors.
We display this content under fair use principles and/or implied license for the purpose of podcast discovery, information, and commentary. We make no claim of ownership over any podcast content, artwork, or related materials shown on this platform. All trademarks, service marks, and trade names are the property of their respective owners.
While we strive to ensure all content usage is properly authorized, if you are a rights holder and believe your content is being used inappropriately or without proper authorization, please contact us immediately at hey@podengine.ai for prompt review and appropriate action, which may include content removal or proper attribution.
By accessing and using this platform, you acknowledge and agree to respect all applicable copyright laws and intellectual property rights of content owners. Any unauthorized reproduction, distribution, or commercial use of the content displayed on this platform is strictly prohibited.