dltHub is a DuckDB-first company, so would appreciate the addition as well
November 20, 2024 at 4:30 PM
dltHub is a DuckDB-first company, so would appreciate the addition as well
Vibe code dltHub Jaffle Shop API: using Curl to get responses for pagination.
With this workflow you allow your agent to grab information that isn't available in docs such as response structure
#dataengineering #databs
www.youtube.com/watch?v=fpNZ...
With this workflow you allow your agent to grab information that isn't available in docs such as response structure
#dataengineering #databs
www.youtube.com/watch?v=fpNZ...
Vibe code dltHub Jaffle Shop API: using Curl to get responses for pagination
YouTube video by dltHub
www.youtube.com
April 19, 2025 at 3:30 AM
Vibe code dltHub Jaffle Shop API: using Curl to get responses for pagination.
With this workflow you allow your agent to grab information that isn't available in docs such as response structure
#dataengineering #databs
www.youtube.com/watch?v=fpNZ...
With this workflow you allow your agent to grab information that isn't available in docs such as response structure
#dataengineering #databs
www.youtube.com/watch?v=fpNZ...
📢 We are hosting a DuckDB meetup in Berlin during the week of the SIGMOD conference.
📍 The meetup will take place on June 26 (Thursday) south of the Tiergarten and will feature talks by Amine Mhedhbi, David Justen and dltHub!
📝 If you plan to attend, please register at duckdb.org/events/2025/...
📍 The meetup will take place on June 26 (Thursday) south of the Tiergarten and will feature talks by Amine Mhedhbi, David Justen and dltHub!
📝 If you plan to attend, please register at duckdb.org/events/2025/...
May 28, 2025 at 3:15 PM
📢 We are hosting a DuckDB meetup in Berlin during the week of the SIGMOD conference.
📍 The meetup will take place on June 26 (Thursday) south of the Tiergarten and will feature talks by Amine Mhedhbi, David Justen and dltHub!
📝 If you plan to attend, please register at duckdb.org/events/2025/...
📍 The meetup will take place on June 26 (Thursday) south of the Tiergarten and will feature talks by Amine Mhedhbi, David Justen and dltHub!
📝 If you plan to attend, please register at duckdb.org/events/2025/...
The shift in data engineering:
The bottleneck is no longer writing pipelines, it’s trusting them in production.
dltHub AI Workbench is built around that:
agents propose, humans verify, tooling enforces.
Works with Claude Code, Cursor, and OpenAI Codex.
The bottleneck is no longer writing pipelines, it’s trusting them in production.
dltHub AI Workbench is built around that:
agents propose, humans verify, tooling enforces.
Works with Claude Code, Cursor, and OpenAI Codex.
Agents can write dlt pipelines. Now they can run & deploy them.
Introducing the dltHub AI Workbench: an infrastructure layer for dltHub that makes AI-generated dlt pipelines trustworthy for production.
dlthub.com
March 24, 2026 at 7:38 PM
The shift in data engineering:
The bottleneck is no longer writing pipelines, it’s trusting them in production.
dltHub AI Workbench is built around that:
agents propose, humans verify, tooling enforces.
Works with Claude Code, Cursor, and OpenAI Codex.
The bottleneck is no longer writing pipelines, it’s trusting them in production.
dltHub AI Workbench is built around that:
agents propose, humans verify, tooling enforces.
Works with Claude Code, Cursor, and OpenAI Codex.
Data platforms deserve SDLC best practices 🚀
✅ Feature branches
✅ CI checks for every PR
✅ Seamless CD to prod
✅ Full lineage in Dagster UI
Built w/:
🔧 dltHub - ELT made simple
💡 dbt - Transformations redefined
⚙️ Dagster - Asset-based orchestration
from community:
medium.com/@jairus-m/th...
✅ Feature branches
✅ CI checks for every PR
✅ Seamless CD to prod
✅ Full lineage in Dagster UI
Built w/:
🔧 dltHub - ELT made simple
💡 dbt - Transformations redefined
⚙️ Dagster - Asset-based orchestration
from community:
medium.com/@jairus-m/th...
The Software Development Lifecycle within a Modern Data Engineering Framework
Utilizing dltHub, dbt, & Dagster+ as a framework for developing data products with software engineering best practices.
medium.com
January 9, 2025 at 4:38 PM
Data platforms deserve SDLC best practices 🚀
✅ Feature branches
✅ CI checks for every PR
✅ Seamless CD to prod
✅ Full lineage in Dagster UI
Built w/:
🔧 dltHub - ELT made simple
💡 dbt - Transformations redefined
⚙️ Dagster - Asset-based orchestration
from community:
medium.com/@jairus-m/th...
✅ Feature branches
✅ CI checks for every PR
✅ Seamless CD to prod
✅ Full lineage in Dagster UI
Built w/:
🔧 dltHub - ELT made simple
💡 dbt - Transformations redefined
⚙️ Dagster - Asset-based orchestration
from community:
medium.com/@jairus-m/th...
entering bluesky with this amazing photo
just dropped off some cognee merch for the dlthub crew
let's make data processing great again!
@matthausk.bsky.social
@datateam.bsky.social
just dropped off some cognee merch for the dlthub crew
let's make data processing great again!
@matthausk.bsky.social
@datateam.bsky.social
December 19, 2024 at 2:24 PM
entering bluesky with this amazing photo
just dropped off some cognee merch for the dlthub crew
let's make data processing great again!
@matthausk.bsky.social
@datateam.bsky.social
just dropped off some cognee merch for the dlthub crew
let's make data processing great again!
@matthausk.bsky.social
@datateam.bsky.social
I personally have a love/hate relationship with SQL - but most AI devs don't want any such thing..they just want to use Python. That's where dltHub comes in as the lead backer behind the open-source dlt library.
venturebeat.com/data-infrast...
venturebeat.com/data-infrast...
Enterprise data engineering revolution: How dltHub's Python open-source platform transforms data pipeline creation for agentic AI | Sean M. Kerner
I personally have a love/hate relationship with SQL - but most AI devs don't want any such thing..they just want to use Python. That's where dltHub comes in as the lead backer behind the open-source d...
www.linkedin.com
November 3, 2025 at 4:13 PM
I personally have a love/hate relationship with SQL - but most AI devs don't want any such thing..they just want to use Python. That's where dltHub comes in as the lead backer behind the open-source dlt library.
venturebeat.com/data-infrast...
venturebeat.com/data-infrast...
🚨 New Video Alert! 🚨
Did you know we're having workshops at #icebergSummit? 😱 Hear from Kevin Liu about the workshop he's putting together with Violetta Mishechkina and Rushan Jiang on getting started with #apacheIceberg using #python.
Did you know we're having workshops at #icebergSummit? 😱 Hear from Kevin Liu about the workshop he's putting together with Violetta Mishechkina and Rushan Jiang on getting started with #apacheIceberg using #python.
March 24, 2025 at 3:04 PM
Loved the energy around Apache Iceberg at the Amsterdam meetup.
At dltHub, we’re focused on making Iceberg actually usable—modernizing legacy stacks with auto-ingestion, schema handling, and pipeline orchestration.
Modernization doesn’t have to hurt.
www.linkedin.com/posts/data-t...
At dltHub, we’re focused on making Iceberg actually usable—modernizing legacy stacks with auto-ingestion, schema handling, and pipeline orchestration.
Modernization doesn’t have to hurt.
www.linkedin.com/posts/data-t...
#apacheiceberg #moderndatastack #datapipelines #dlthub | Adrian Brudaru
Violetta’s talk with Lakekeeper showed exactly what we’re focused on at dltHub: making Iceberg actually usable, by modernizing your data stack and automating ingestion, schema evolution, and pipeline ...
www.linkedin.com
April 3, 2025 at 9:53 AM
Loved the energy around Apache Iceberg at the Amsterdam meetup.
At dltHub, we’re focused on making Iceberg actually usable—modernizing legacy stacks with auto-ingestion, schema handling, and pipeline orchestration.
Modernization doesn’t have to hurt.
www.linkedin.com/posts/data-t...
At dltHub, we’re focused on making Iceberg actually usable—modernizing legacy stacks with auto-ingestion, schema handling, and pipeline orchestration.
Modernization doesn’t have to hurt.
www.linkedin.com/posts/data-t...
🚀 Looking into DuckDB, S3, Iceberg, Delta and data catalogs ?
If so, then consider our dltHub Open Data Lakes Gathering with Foundation Capital on Nov 6 in San Francisco.
Join
@spite.vc , Alex Butler & Marcin Rudolf for demos & networking.
👉 RSVP events.foundationcap.com/foundation-c...
If so, then consider our dltHub Open Data Lakes Gathering with Foundation Capital on Nov 6 in San Francisco.
Join
@spite.vc , Alex Butler & Marcin Rudolf for demos & networking.
👉 RSVP events.foundationcap.com/foundation-c...
October 28, 2024 at 4:47 PM
🚀 Looking into DuckDB, S3, Iceberg, Delta and data catalogs ?
If so, then consider our dltHub Open Data Lakes Gathering with Foundation Capital on Nov 6 in San Francisco.
Join
@spite.vc , Alex Butler & Marcin Rudolf for demos & networking.
👉 RSVP events.foundationcap.com/foundation-c...
If so, then consider our dltHub Open Data Lakes Gathering with Foundation Capital on Nov 6 in San Francisco.
Join
@spite.vc , Alex Butler & Marcin Rudolf for demos & networking.
👉 RSVP events.foundationcap.com/foundation-c...
Continuing with my series on Tobiko's SQLMesh and building on the work I've done this week so far using dltHub and @duckdb.org. I also get to enjoy Harlequin.sh for the first time as a great way to explore DuckDB data in the terminal.
open.substack.com/pub/davidsj/...
open.substack.com/pub/davidsj/...
sqlmesh init -t dlt --dlt-pipeline bluesky duckdb
dlt metadata -> sqlmesh models
open.substack.com
December 5, 2024 at 5:09 PM
Continuing with my series on Tobiko's SQLMesh and building on the work I've done this week so far using dltHub and @duckdb.org. I also get to enjoy Harlequin.sh for the first time as a great way to explore DuckDB data in the terminal.
open.substack.com/pub/davidsj/...
open.substack.com/pub/davidsj/...
I've had a crazy few days with my advent calendar of code, looking at Tobiko's SQLMesh with @duckdb.org.
Yesterday, I mentioned in my post that I needed to bring in some data from @bsky.app's HTTP endpoints, and I was going to try using dltHub.
davidsj.substack.com/p/dlt-windsu...
Yesterday, I mentioned in my post that I needed to bring in some data from @bsky.app's HTTP endpoints, and I was going to try using dltHub.
davidsj.substack.com/p/dlt-windsu...
dlt windsurfing
Trying out dlt with DuckDB
davidsj.substack.com
December 4, 2024 at 7:54 PM
I've had a crazy few days with my advent calendar of code, looking at Tobiko's SQLMesh with @duckdb.org.
Yesterday, I mentioned in my post that I needed to bring in some data from @bsky.app's HTTP endpoints, and I was going to try using dltHub.
davidsj.substack.com/p/dlt-windsu...
Yesterday, I mentioned in my post that I needed to bring in some data from @bsky.app's HTTP endpoints, and I was going to try using dltHub.
davidsj.substack.com/p/dlt-windsu...
The craziest part of the new dltHub AI release? The MCP integration.
Asked Claude Code for an OpenAI pipeline -> it searches the dlt context -> scaffolds the exact code with schema & incremental loading. No more starting from scratch.
https://dlthub.com/blog/ai-workbench
Asked Claude Code for an OpenAI pipeline -> it searches the dlt context -> scaffolds the exact code with schema & incremental loading. No more starting from scratch.
https://dlthub.com/blog/ai-workbench
March 26, 2026 at 6:32 PM
The craziest part of the new dltHub AI release? The MCP integration.
Asked Claude Code for an OpenAI pipeline -> it searches the dlt context -> scaffolds the exact code with schema & incremental loading. No more starting from scratch.
https://dlthub.com/blog/ai-workbench
Asked Claude Code for an OpenAI pipeline -> it searches the dlt context -> scaffolds the exact code with schema & incremental loading. No more starting from scratch.
https://dlthub.com/blog/ai-workbench
March 11, 2025 at 4:39 PM
Agent Distillation.
Same traces, different outcome.
Turn them into training-ready datasets for smaller, task-specific models, built together with distil labs.
Browse the Blueprints:
Same traces, different outcome.
Turn them into training-ready datasets for smaller, task-specific models, built together with distil labs.
Browse the Blueprints:
dltHub Blueprints
dltHub is a composable data platform. Blueprints are its ready-made models: each one dltHub assembled for a specific use case, end to end, from the sources you already use to a production dashboard or API.
dlthub.com
July 10, 2026 at 1:40 PM
Agent Distillation.
Same traces, different outcome.
Turn them into training-ready datasets for smaller, task-specific models, built together with distil labs.
Browse the Blueprints:
Same traces, different outcome.
Turn them into training-ready datasets for smaller, task-specific models, built together with distil labs.
Browse the Blueprints:
Excited to share that I've built my first end-to-end data pipeline using @dlthub, @getdbt.com , @PrefectIO, and @clickhouse.com ! Big thanks to the @coursera course that provided the foundation, to @joereis.bsky.social and @NgZern7119 for sharing invaluable resources along the way. 🙇
December 29, 2025 at 2:41 AM
Excited to share that I've built my first end-to-end data pipeline using @dlthub, @getdbt.com , @PrefectIO, and @clickhouse.com ! Big thanks to the @coursera course that provided the foundation, to @joereis.bsky.social and @NgZern7119 for sharing invaluable resources along the way. 🙇
How much data can $1 of compute move?
We benchmarked dltHub on a small worker (2 vCPU / 4 GB) loading into BigQuery:
Parquet: ~170 GB
Postgres: ~65 GB
JSON: ~4.6 GB
REST: whatever the API allows
Methodology + results ↓
https://dlthub.com/blog/benchmark-dlthub
We benchmarked dltHub on a small worker (2 vCPU / 4 GB) loading into BigQuery:
Parquet: ~170 GB
Postgres: ~65 GB
JSON: ~4.6 GB
REST: whatever the API allows
Methodology + results ↓
https://dlthub.com/blog/benchmark-dlthub
June 9, 2026 at 4:28 PM
How much data can $1 of compute move?
We benchmarked dltHub on a small worker (2 vCPU / 4 GB) loading into BigQuery:
Parquet: ~170 GB
Postgres: ~65 GB
JSON: ~4.6 GB
REST: whatever the API allows
Methodology + results ↓
https://dlthub.com/blog/benchmark-dlthub
We benchmarked dltHub on a small worker (2 vCPU / 4 GB) loading into BigQuery:
Parquet: ~170 GB
Postgres: ~65 GB
JSON: ~4.6 GB
REST: whatever the API allows
Methodology + results ↓
https://dlthub.com/blog/benchmark-dlthub
🚀 In the last 6 months we have seen early adopters in the dlt community take advantage of AI code editors such as Cursor. Check our initial assistants and building blocks for custom workflows such as Anthropic MCP servers for dlt on the recently launched hub.continue.dev/dlthub from @continue.dev 🚀
March 13, 2025 at 6:40 PM
🚀 In the last 6 months we have seen early adopters in the dlt community take advantage of AI code editors such as Cursor. Check our initial assistants and building blocks for custom workflows such as Anthropic MCP servers for dlt on the recently launched hub.continue.dev/dlthub from @continue.dev 🚀
The new dltHub AI Workbench Data Quality Toolkit starts from context your pipeline already knows: schema contracts, keys, constraints, and sampled values.
Plain-language business rules → checks that run on every load.
Plain-language business rules → checks that run on every load.
dltHub AI Workbench data quality toolkit: schema-aware checks that route their own fixes
Preview of the dltHub AI Workbench data quality toolkit: schema-bootstrapped checks, column sampling before any rule ships, decorators that run inside pipeline.run(), and routing of failures back to the toolkit that owns the surface area.
dlthub.com
June 5, 2026 at 1:07 PM
The new dltHub AI Workbench Data Quality Toolkit starts from context your pipeline already knows: schema contracts, keys, constraints, and sampled values.
Plain-language business rules → checks that run on every load.
Plain-language business rules → checks that run on every load.
I hate dealing with Python environments, so I invested in tower.dev (spite driven investing?). They're cleaning up Python operations, environments, and tooling up (at least for data).
They've made quite a bit of progress already. I'm pretty excited about where this is going.
They've made quite a bit of progress already. I'm pretty excited about where this is going.
The 10x data team at Taktile, enabled by Tower and dltHub
YouTube video by Tower
www.youtube.com
December 6, 2024 at 7:21 PM
I hate dealing with Python environments, so I invested in tower.dev (spite driven investing?). They're cleaning up Python operations, environments, and tooling up (at least for data).
They've made quite a bit of progress already. I'm pretty excited about where this is going.
They've made quite a bit of progress already. I'm pretty excited about where this is going.
✨ OSS Enterprise success story time!
Stellantis (14 car brands including Jeep & Maserati) is using @dlt to:
- Cut 60+ data tools down to 4
- Speed up pipelines by 66%
- Onboard devs in 2hrs
Open source eating enterprise, one pipeline at a time 🚀
Check it out here!
www.youtube.com/watch?v=Kj3E...
Stellantis (14 car brands including Jeep & Maserati) is using @dlt to:
- Cut 60+ data tools down to 4
- Speed up pipelines by 66%
- Onboard devs in 2hrs
Open source eating enterprise, one pipeline at a time 🚀
Check it out here!
www.youtube.com/watch?v=Kj3E...
Navigating Enterprise ELT towards Data Democracy and Cost Efficiency by Stellantis - dltHub Paris
YouTube video by dltHub
www.youtube.com
January 22, 2025 at 8:23 AM
✨ OSS Enterprise success story time!
Stellantis (14 car brands including Jeep & Maserati) is using @dlt to:
- Cut 60+ data tools down to 4
- Speed up pipelines by 66%
- Onboard devs in 2hrs
Open source eating enterprise, one pipeline at a time 🚀
Check it out here!
www.youtube.com/watch?v=Kj3E...
Stellantis (14 car brands including Jeep & Maserati) is using @dlt to:
- Cut 60+ data tools down to 4
- Speed up pipelines by 66%
- Onboard devs in 2hrs
Open source eating enterprise, one pipeline at a time 🚀
Check it out here!
www.youtube.com/watch?v=Kj3E...
Thanks to @lhoestq.hf.co and the @hf.co datasets team for the collaboration.
Launch blog:
https://dlthub.com/blog/hugging-face-dlt-ml
#DataEngineering #MachineLearning #LLMOps
Launch blog:
https://dlthub.com/blog/hugging-face-dlt-ml
#DataEngineering #MachineLearning #LLMOps
Hugging Face x dltHub: The missing data layer for ML
From raw data to production ML: load, transform, embed, and publish curated datasets with declarative pipelines powered by dltHub.
dlthub.com
March 15, 2026 at 11:47 AM
Thanks to @lhoestq.hf.co and the @hf.co datasets team for the collaboration.
Launch blog:
https://dlthub.com/blog/hugging-face-dlt-ml
#DataEngineering #MachineLearning #LLMOps
Launch blog:
https://dlthub.com/blog/hugging-face-dlt-ml
#DataEngineering #MachineLearning #LLMOps
🚀 Live Event w MotherDuck & dltHub: Fast & Scalable Analytics Pipelines
📅 Feb 26 | 17:00 CET | Zoom
🔹 Easy data ingestion
🔹 Custom ETL pipelines in Python
🔹 Smooth transition from DuckDB to MotherDuck
🔥 Live demo + Q&A!
🔗 Register: lu.ma/79a7lysr?utm...
#databs
📅 Feb 26 | 17:00 CET | Zoom
🔹 Easy data ingestion
🔹 Custom ETL pipelines in Python
🔹 Smooth transition from DuckDB to MotherDuck
🔥 Live demo + Q&A!
🔗 Register: lu.ma/79a7lysr?utm...
#databs
Fast & Scalable Analytics Pipelines with MotherDuck & dltHub · Zoom · Luma
Modern data pipelines require speed and scalability. In this session, you'll see how dltHub’s open-source ETL capabilities simplify extracting and loading data…
lu.ma
February 14, 2025 at 1:12 PM
🚀 Live Event w MotherDuck & dltHub: Fast & Scalable Analytics Pipelines
📅 Feb 26 | 17:00 CET | Zoom
🔹 Easy data ingestion
🔹 Custom ETL pipelines in Python
🔹 Smooth transition from DuckDB to MotherDuck
🔥 Live demo + Q&A!
🔗 Register: lu.ma/79a7lysr?utm...
#databs
📅 Feb 26 | 17:00 CET | Zoom
🔹 Easy data ingestion
🔹 Custom ETL pipelines in Python
🔹 Smooth transition from DuckDB to MotherDuck
🔥 Live demo + Q&A!
🔗 Register: lu.ma/79a7lysr?utm...
#databs