Top all-time · #6933
dltHub
Company blog · dlthub.com/blogdataprogramming
dltHub is the company blog at dlthub.com, writing about data and programming. Since 2023, 12 different Hacker News readers have linked it 23 times. It is still writing: the last post was on 2026-10-29, and you can follow it by feed.
Too few sampled comments (7) to say how often HN recommends it.?
Why HN links it
HN readers link dlthub.com for the dlt open-source Python library for loading data into datasets and pipelines, including its docs, destinations, and ETL use cases. Commenters point to it as a tool, not as writing.
Summarised by Claude from a sample of 7 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
dlt is the open-source Python library 50,000s of developers use to build data pipelines. dltHub is the agentic platform that deploys, monitors, and scales them.
What Hacker News says?
Run data integration pipelines with Github actions - https://dlthub.com/docs/walkthroughs/deploy-a-pipeline/deplo... It's the easiest way for many startups to get people to try out your software for free.
Comment linking /docs/walkthroughs/deploy-a-pipeline/deploy-with-github-actions
on “Bypassing GitHub Actions policies in the dumbest way possible”Submitted Build Dashboards Using Claude Code and Dlt as a story · 2 points
HN discussionIf you're looking for "open source Python ETL", two things that are better options: https://dlthub.com/ https://hub.meltano.com/ we[0] use meltano in production and I'm happy with it. I've played around with dlt and it's great, just not a ton of sources yet. 0 - https://www.definite.app/
Comment linking /
on “Open Source Python ETL”Submitted Data Platform Engineers: The Game-Changers of Data Teams as a story · 2 points
HN discussionlooks like dlt doesn't support it as a destination (which this is a wrapper around) https://dlthub.com/docs/dlt-ecosystem/destinations/
Comment linking /docs/dlt-ecosystem/destinations/
on “Show HN: I built an open-source data copy tool called ingestr”Submitted Agents can write dlt pipelines. Now they can run and deploy them as a story · 1 points
HN discussionPerhaps look into using dlt from https://dlthub.com , using pyarrow or polars. It handles large datasets well, especially when using generators to process the data in chunks.
Comment linking /
on “The Birth of Parquet”Submitted Show HN: We built a LLM-native workflow with 3500 scaffolds and a debug app as a story · 1 points
HN discussionwe actually spent several weeks writing openAPI -> dlt pipeline converter. you can check what've got here: https://github.com/dlt-hub/dlt-init-openapi we'll continue this project but I learnt from it that most of the openAPI specs are a mess with hundreds of endpoints, incomplete definitions, lack of relations between endpoints, unique constraints etc. so there's tons of heuristics needed anyway. but sometimes it wo…
Comment linking /docs/walkthroughs/adjust-a-schema
on “Show HN: Data load tool(dlt)-Python library to automate the creation of datasets”Submitted DltHub: LLM-native data platform for Python devs to build/run pipelines as a story · 1 points
HN discussionPotential conflict with other quite popular Python library: https://dlthub.com/docs/intro
Comment linking /docs/intro
on “Show HN: Data load tool(dlt)-Python library to automate the creation of datasets”Submitted Orchestrators: You Are All Right, but You Are All Wrong Too as a story · 1 points
HN discussionPulling from and into production databases is one of the early favourites from our dlt user base. Some reasons explained here in this MongoDB example ( https://dlthub.com/docs/blog/MongoDB-dlt-Holistics )
Comment linking /docs/blog/MongoDB-dlt-Holistics
on “Show HN: Data load tool(dlt)-Python library to automate the creation of datasets”for now :) Thanks for pointing it out - and it looks like we should add an aws lambda guide too :) If you want to deploy to lambda, try asking in the slack community, some folks there do it. Or if you wanna try yourself, here is a similar guide that highlights some concerns from deploying on gcp cloud functions https://dlthub.com/docs/walkthroughs/deploy-a-pipeline/deplo...
Comment linking /docs/walkthroughs/deploy-a-pipeline/deploy-with-google-cloud-functions
on “Show HN: Data load tool(dlt)-Python library to automate the creation of datasets”There are multiple ways to run together - we will show a few in a demo coming out soon. We also consider a tighter integration like with Airflow described here as a possible next step https://dlthub.com/docs/walkthroughs/deploy-a-pipeline/deplo... We will investigate the interest incrementally as to not build any plugins that don't end up used.
Comment linking /docs/walkthroughs/deploy-a-pipeline/deploy-with-airflow-composer
on “Show HN: Data load tool(dlt)-Python library to automate the creation of datasets”1) Yes. We support all the databases and buckets as data sources as well. Some examples: - get data from any sql database: https://dlthub.com/docs/dlt-ecosystem/verified-sources/sql_d... or https://dlthub.com/docs/getting-started#load-data-from-a-var... - do it super quickly with pyarrow: https://dlthub.com/docs/examples/connector_x_arrow/ - get data from any storage bucket: https://github.com/dlt-hub/verified-sourc…
Comment linking /docs/examples/connector_x_arrow/
on “Show HN: Data load tool(dlt)-Python library to automate the creation of datasets”You can use pydantic models to define schemas, validate data (we also load instances of the models natively): https://dlthub.com/docs/general-usage/resource#define-a-sche... We have a PR ( https://github.com/dlt-hub/dlt/pull/594 ) that is about to merge that makes the above highly configurable, between evolution and hard stopping: - you will be able to totally freeze schema and reject bad rows - or accept the data f…
Comment linking /docs/general-usage/resource
on “Show HN: Data load tool(dlt)-Python library to automate the creation of datasets”first you extract and load data with dlt and then you transform them with dbt. so both tools work very well together. we did a really cool helper to make it easier( https://dlthub.com/docs/dlt-ecosystem/transformations/dbt/ ) (I'm one of core devs in dltHub)
Comment linking /docs/dlt-ecosystem/transformations/dbt/
on “Show HN: Data load tool(dlt)-Python library to automate the creation of datasets”
