PodcastsRank #1343
Artwork for Data Engineering Podcast

Data Engineering Podcast

TechnologyPodcastsEducationENunited-statesSeveral times per week
4.5 / 5126 ratings
This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.
Top 2.7% by pitch volume (Rank #1343 of 50,000)Data updated Feb 10, 2026

Key Facts

Publishes
Several times per week
Episodes
500
Founded
N/A
Category
Technology
Number of listeners
Private
Hidden on public pages

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Public snapshot
Audience: 40K–100K / month
Canonical: https://podpitch.com/podcasts/data-engineering-podcast
Cadence: Active weekly
Reply rate: 35%+

Latest Episodes

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Branches, Diffs, and SQL: How Dolt Powers Agentic Workflows

Sun Feb 01 2026

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Summary  In this episode Tim Sehn, founder and CEO of DoltHub, talks about Dolt - the world’s first version‑controlled SQL database - and why Git‑style semantics belong at the heart of data systems and AI workflows. Tim explains how Dolt combines a MySQL/Postgres‑compatible interface with a novel storage engine built on a “Prollytree” to enable fast, row‑level branching, merging, and diffs of both schema and data. He digs into real production use cases: powering applications that expose version control to end users, reproducible ML feature stores, managing massive configuration for games, and enabling safe agentic writes via branch‑based review flows. He compares Dolt’s approach to LakeFS, Neon, and PlanetScale, and explores developer workflows unlocked by decentralized clones, full audit logs, and PR‑style data reviews.  Announcements  Hello and welcome to the Data Engineering Podcast, the show about modern data managementIf you lead a data team, you know this pain: Every department needs dashboards, reports, custom views, and they all come to you. So you're either the bottleneck slowing everyone down, or you're spending all your time building one-off tools instead of doing actual data work. Retool gives you a way to break that cycle. Their platform lets people build custom apps on your company data—while keeping it all secure. Type a prompt like 'Build me a self-service reporting tool that lets teams query customer metrics from Databricks—and they get a production-ready app with the permissions and governance built in. They can self-serve, and you get your time back. It's data democratization without the chaos. Check out Retool at dataengineeringpodcast.com/retool today and see how other data teams are scaling self-service. Because let's be honest—we all need to Retool how we handle data requests.Your host is Tobias Macey and today I'm interviewing Tim Sehn about Dolt, a version controlled database engine and its applications for agentic workflows Interview   IntroductionHow did you get involved in the area of data management?Can you describe what Dolt is and the story behind it?What are the key use cases that you are focused on solving by adding version control to the database layer?There are numerous projects related to different aspects of versioning in different data contexts (e.g. LakeFS, Datomic, etc.). What are the versioning semantics that you are focused on?You position Dolt as "the database for AI". How does data versioning relate to AI use cases?What types of AI systems are able to make best use of Dolt's versioning capabilities?Can you describe how Dolt and Doltgres are implemented?How have the design and scope of the project changed since you first started working on it?What are some of the architecture and integration patterns around relational databases that change when you introduce version control semantics as a core primitive?What are some anti-patterns that you have seen teams develop around Dolt's versioning functionality?What are the most interesting, innovative, or unexpected ways that you have seen Dolt used?What are the most interesting, unexpected, or challenging lessons that you have learned while working on Dolt?When is Dolt the wrong choice?What do you have planned for the future of Dolt? Contact Info   LinkedIn 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 AI Engineering Podcast is your guide to the fast-moving world of building AI systems.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. Links   DoltDoltHubStockmarket DataLakeFSDatomicGitMySQLProlly TreeNeonDjangoFeature StoreMCP ServerNessieIcebergPlanetScaleO(NlogN) Big O ComplexityB-TreeGit MergeGit RebaseAST == Abstract Syntax TreeSupabaseCockroachDBDocument DatabaseMongoDBGastownBeads The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

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Summary  In this episode Tim Sehn, founder and CEO of DoltHub, talks about Dolt - the world’s first version‑controlled SQL database - and why Git‑style semantics belong at the heart of data systems and AI workflows. Tim explains how Dolt combines a MySQL/Postgres‑compatible interface with a novel storage engine built on a “Prollytree” to enable fast, row‑level branching, merging, and diffs of both schema and data. He digs into real production use cases: powering applications that expose version control to end users, reproducible ML feature stores, managing massive configuration for games, and enabling safe agentic writes via branch‑based review flows. He compares Dolt’s approach to LakeFS, Neon, and PlanetScale, and explores developer workflows unlocked by decentralized clones, full audit logs, and PR‑style data reviews.  Announcements  Hello and welcome to the Data Engineering Podcast, the show about modern data managementIf you lead a data team, you know this pain: Every department needs dashboards, reports, custom views, and they all come to you. So you're either the bottleneck slowing everyone down, or you're spending all your time building one-off tools instead of doing actual data work. Retool gives you a way to break that cycle. Their platform lets people build custom apps on your company data—while keeping it all secure. Type a prompt like 'Build me a self-service reporting tool that lets teams query customer metrics from Databricks—and they get a production-ready app with the permissions and governance built in. They can self-serve, and you get your time back. It's data democratization without the chaos. Check out Retool at dataengineeringpodcast.com/retool today and see how other data teams are scaling self-service. Because let's be honest—we all need to Retool how we handle data requests.Your host is Tobias Macey and today I'm interviewing Tim Sehn about Dolt, a version controlled database engine and its applications for agentic workflows Interview   IntroductionHow did you get involved in the area of data management?Can you describe what Dolt is and the story behind it?What are the key use cases that you are focused on solving by adding version control to the database layer?There are numerous projects related to different aspects of versioning in different data contexts (e.g. LakeFS, Datomic, etc.). What are the versioning semantics that you are focused on?You position Dolt as "the database for AI". How does data versioning relate to AI use cases?What types of AI systems are able to make best use of Dolt's versioning capabilities?Can you describe how Dolt and Doltgres are implemented?How have the design and scope of the project changed since you first started working on it?What are some of the architecture and integration patterns around relational databases that change when you introduce version control semantics as a core primitive?What are some anti-patterns that you have seen teams develop around Dolt's versioning functionality?What are the most interesting, innovative, or unexpected ways that you have seen Dolt used?What are the most interesting, unexpected, or challenging lessons that you have learned while working on Dolt?When is Dolt the wrong choice?What do you have planned for the future of Dolt? Contact Info   LinkedIn 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 AI Engineering Podcast is your guide to the fast-moving world of building AI systems.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. Links   DoltDoltHubStockmarket DataLakeFSDatomicGitMySQLProlly TreeNeonDjangoFeature StoreMCP ServerNessieIcebergPlanetScaleO(NlogN) Big O ComplexityB-TreeGit MergeGit RebaseAST == Abstract Syntax TreeSupabaseCockroachDBDocument DatabaseMongoDBGastownBeads The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA

Key Metrics

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Pitches sent
84
From PodPitch users
Rank
#1343
Top 2.7% by pitch volume (Rank #1343 of 50,000)
Average rating
4.5
From 126 ratings
Reviews
14
Written reviews (when available)
Publish cadence
Several times per week
Active weekly
Episode count
500
Data updated
Feb 10, 2026
Social followers
4.8K

Public Snapshot

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Country
United States
Language
English
Language (ISO)
Release cadence
Several times per week
Latest episode date
Sun Feb 01 2026

Audience & Outreach (Public)

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Audience range
40K–100K / month
Public band
Reply rate band
35%+
Public band
Response time band
30+ days
Public band
Replies received
1–5
Public band

Public ranges are rounded for privacy. Unlock the full report for exact values.

Presence & Signals

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Social followers
4.8K
Contact available
Yes
Masked on public pages
Sponsors detected
Yes
Guest format
Yes

Social links

No public profiles listed.

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Monthly listeners49,360
Reply rate18.2%
Avg response4.1 days
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4.5 / 5126 ratings
Ratings126
Written reviews14

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Frequently Asked Questions About Data Engineering Podcast

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What is Data Engineering Podcast about?

This show goes behind the scenes for the tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation are just some of the topics that you will find here.

How often does Data Engineering Podcast publish new episodes?

Several times per week

How many listeners does Data Engineering Podcast get?

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