Adrian Brudaru

We’ll go beyond basic ETL:

- Handling nested & evolving schemas
- Accelerating pipeline creation with LLMs
- Moving from scripts to reliable ingestion workflows
- Validating data and schema changes using the dlt dashboard and dlt MCP

From APIs to Warehouses: AI-Assisted Data Ingestion with dlt · Luma This hands-on workshop focuses on building reliable data ingestion pipelines to data warehouses (for example, Snowflake) using dlt (data load tool), enhanced…

From APIs to Warehouses 📦

On Feb 17 (16:30 CET), together with DataTalks.Club, Aashish Nair will walk through building end-to-end ingestion pipelines with dlt, from raw APIs to production-ready warehouse loads.

Register here 👇

The Last Mile is Solved by Slop I didn't vibe-build a product. I wrote a messy scaffold that runs a pipeline, grabs the schema, and forces an agent to build a star schema. It works shockingly well.

What if dimensional modeling didn’t mean hours of boilerplate SQL?

We built an AI workflow that turns raw data into semantic models in minutes, powered by 20 questions.

Rethinking data transformation 👇

Who’s speaking in Berlin 👇

- Francesco Mucio: integrating 20+ APIs
- Bijan Soltani: real-world analytics
- Nemanja Bibic: ingestion for AI memory
- Ken Schröder: analyst-friendly ingestion w/ dlt on AWS
- Violetta Mishechkina: AI agents, data quality & what’s next

See you there 🚀

dltHub Community Meetup in Berlin with Cognee, Untitled Data Company, Gemma Analytics & Babbel · Luma Join us for the dltHub Community Meetup in Berlin. This evening is for curious minds who want to learn more about what we’re building at dltHub. We’ll share a…

Berlin, it’s meetup time!

Join us for the dltHub Community Meetup, an evening of real-world demos, lessons learned, and conversations with builders.

📍 Rosebud, Berlin
📆 Feb 17 | 18:00 – 21:00

Curious about what we’re building at dltHub? Come by 👋

Production pipelines don’t fail loudly, they drift.

Feb 12 · 16:00 CET - Online
Hands-on workshop on operating pipelines in production:
• schema changes
• backfills
• CI/CD
• long-term reliability

Register → https://community.dlthub.com/workshop-maintaining-servicing-production-data-pipelines

💘 Data Valentine Challenge started today.

5 days. 5 live data sessions with: 
@datarecce.bsky.social, Greybeam, @databasetycoon.bsky.social, @bauplan.bsky.social

Our slot: Wednesday → Pipelines That Don’t Ghost You

Feb 9–13 | 9am PT | Online

https://reccehq.com/data-valentine-week-challenge/

• Markets (Kalshi, Polymarket, DEX Screener)
• AI platforms (fal, Jina AI, Kie AI)
• Macro data (World Bank, Finnhub, Alpha Vantage, Frankfurter)
• Entertainment (PokéAPI, OpenF1)

Explore the contexts 👇

January’s Rising Stars in the dlt ecosystem 👇

Builders are vibe coding pipelines around real-time markets, AI dev platforms, macro data, and more.

What’s trending right now:

3.7x Faster Pipelines: Benchmarking Arrow & ADBC vs. SQLAlchemy for EL Moved 5M rows from DuckDB to MySQL 3.7x faster, reducing time from 344s to 92s by switching from SQLAlchemy’s row-by-row path to Arrow + ADBC’s columnar pipeline.

Arrow + ADBC + dlt just broke the EL speed limit.

5M rows DuckDB→MySQL:
SQLAlchemy 344s
Arrow + ADBC 92s (3.7× faster)

One line of code. Columnar end-to-end.

Benchmarks:

The Builder: Outliving the Modern Data Stack We were told that democratization meant 'safety,' but all we got were expensive cages. The era of the SaaS hostage is ending; the era of the sovereign Builder has begun.

The Modern Data Stack™ was a comfy lie that turned data engineers into passive consumers, now the bill's due, market's schisming into vendor-locked hell vs builder freedom.

Read the Builder's Manifesto:

📍 Amsterdam
🗓 Jan 29 · 3–6 PM (GMT+1)

Agenda highlights:
• Vision — Matthaus Krzykowski (@matthausk.bsky.social) & Julian Alves | dltHub
• Demos — Vincent D. Warmerdam (@koaning.bsky.social) | Marimo, Mehdi Ouazza (@mehdio.com) | MotherDuck
• First impressions — Thomas in't Veld | Tasman Analytics

Together with @motherduck.com, @duckdb.org, and marimo, we’re bringing together a toolkit built for full-stack data developers:
🔹 ingest with dlt
🔹 query fast
🔹 serve instantly

Built for builders, not enterprise overhead.

dltHub ❤️ Marimo ❤️ MotherDuck · Luma dltHub and Marimo and MotherDuck are having a child. What are looking at? dltHub provides the ELT, runtime, and execution layer, turning production data…

Want to influence the tools you use every day?

We’re hosting a Builder’s Data Stack meetup focused on developer flow, fast iteration, and shaping the roadmap with the community.

Pull up a chair:

The Plutonium Protocol: Engineering Safety for the LLM Intern Era The “data is oil” era is over. With LLMs, data is plutonium: powerful, toxic. Shift left and secure the reactor with 5 quality pillars.

An AI agent ignored a code freeze, wiped a prod DB, then hallucinated data to cover it up.

Data quality in the LLM era isn’t optional, it’s a safety problem.

We call it data as plutonium - powerful and dangerous without containment.

🎤 Call for Speakers
Using dlt in your projects? We’re opening the mic to the community for short 10–15 min talks sharing:
🛠️ real use cases
📚 lessons learned

If this sounds like you, reach out via the event page.

Let’s learn from each other in Paris!

dlt Paris Community Meetup #2 with dltHub & Polycea · Luma Join us for an evening of community and conversation! Co-hosted by dltHub and Polycea, this meetup brings people together for short talks and networking with…

🇫🇷 Paris data folks 💛

We’re hosting a dlt Community Meetup in Paris on Feb 4th (6–9 PM) together with Polycea.

A community meetup focused on practical takeaways, shared learnings, and conversations with people using dlt hands-on.

Join us here:

Data quality is the vegetables of data engineering: everyone agrees it's important, but nobody wants to implement it.

To increase your 𝚟̶𝚎̶𝚐̶𝚎̶𝚝̶𝚊̶𝚋̶𝚕̶𝚎̶ ̶𝚒̶𝚗̶𝚝̶𝚊̶𝚔̶𝚎̶ test coverage, check out these 11 delicious recipes.

https://dlthub.com/blog/practical-data-quality-recipes-with-dlt

This gives you a self-healing system that keeps your semantic layer in sync as your data changes.

Huge thanks to Julien Hurault and Hussain Sultan for their contributions.

The blueprint:
1️⃣ ingest with dlt to capture metadata
2️⃣ use LLMs to infer semantic relationships
3️⃣ auto-generate the BI layer

We went from a raw Sakila DB to a governed semantic layer automatically. Moving beyond manual mappings to automate the context itself.

Autofiling the Boring Semantic Layer: From Sakila to Chat-BI with dltHub Build one semantic model and reuse it across APIs, chatbots, and apps. Let LLMs handle the tedious mapping so you can ship data products that quietly just work.

Semantic layers are the most important "boring" part of data. 

Building them manually is a bottleneck for Chat-BI. dlt is changing the game by "autofilling" the metadata gap, turning months of modeling into minutes of automation. 

Most data quality failures happen because checks come too late.

dlt + dltHub treat quality as a lifecycle: in-flight checks, safe staging, and production monitoring.

Catch issues earlier, fix less and trust your data more.

docs: https://dlthub.com/docs/general-usage/data-quality-lifecycle

Dlt+ClickHouse+Rill: Multi-Cloud Cost Analytics, Cloud-Ready FinOps Made Easy: A Starter Repo to Oversee Cloud Costs from Different Hyperscalers.

@ssp.sh drops another great deep-dive, a declarative data stack dlt + @clickhouse.com + @rilldata.com that simplifies tracking cloud spend across multiple platforms.

A complete cloud-native FinOps setup in minutes.

🔗 Explore the full walkthrough

Snowflake for Startups Pitch Night · Luma Join Snowflake for Startups and Proving Ground for an evening of innovation and networking at the SVAI Hub. This pitch night is a chance to see some of the Bay…

We're thrilled to take the stage at the Snowflake for Startups Pitch Night!

Join us at the Silicon Valley AI Hub to see how dlt's code & LLM-first infra-native data ingestion library is the fastest way to get compliant data into Snowflake.

Convergence: The Anti-Entropy Engine Most LLM runs don’t fail. They converge fast, and the secret isn’t smarter models but better scaffolds that guide the work instead of forcing it.

AI workflows break on LLM updates?

Our Anti-Entropy pattern fixes this with declarative scaffolds, error loops, and dashboards for antifragile convergence.

Saves time, acts like an invisible senior engineer.

Ditch crutches, skip the ‘Deer in Headlights’ panic!

Each integration came together quickly: Stripe with just a token, AWS CUR from S3, and GCP billing straight from BigQuery.

This powerful tool stack combined with dlt's connectors, @duckdb.org and @rilldata.com's interactive dashboards, deliver a real-time, consolidated analytics view.

At the core is a single incremental pipeline powered by dlt, loading everything into Parquet & DuckDB for fast analysis.

Handling auth, pagination, and schema changes, the pipeline remains simple end to end, and because it’s fully pluggable, adding Azure or Cloudflare is easy.

Multi-Cloud Cost Analytics: From Cost-Export to Parquet to Rill Learn how to unify AWS and GCP costs with revenue data in a single dashboard. Step-by-step guide using dlt, Parquet, and Rill. Clone and run immediately.

To overcome complex cloud cost analysis, @ssp.sh showed how dlt can ingest and normalize AWS, GCP, and Stripe data into a unified cost dashboard.

The result is a single view for ROI analysis powered by a simple ELT.

Check out the full solution! 👇

Motherduck Europe & dlt DuckLake support MotherDuck lands in Europe with serverless DuckDB warehousing. dlt adds DuckLake support, giving EU teams a fast, modern data stack.

European data teams can enjoy lightning-fast analytics & production-ready pipelines with @motherduck EU region fully available.

Choose loading via MotherDuck or dlt's native DuckLake destination → support for Postgres, DuckDB, SQLite, MySQL.

Ever launched a data pipeline & wondered what’s happening under the hood? The dlt Workspace Dashboard gives real-time visibility into pipeline state, schemas, live dataset queries, run traces → all in one web app. Built with 
@marimo.io. 
Try it now: 👉 https://dlthub.com/docs/general-usage/dashboard