# How dlt datasets support portable data pipelines

DevFeed: [How dlt datasets support portable data pipelines](<https://devfeed.tech/articles/a-normie-s-guide-to-portable-data-pipelines-80278.md>)

Original publisher: [Read original article](<https://dlthub.com/blog/datasets2>)

Author: Adrian Brudaru

Published: 2025-05-13T00:00:00Z

Content type: tutorial

Language: en

Sources: [DLT Hub](<https://devfeed.tech/sources/dlt-hub.md>)

Topics: [data-engineering](<https://devfeed.tech/topics/data-engineering.md>), [Data pipelines](<https://devfeed.tech/topics/data-pipelines.md>), [etl](<https://devfeed.tech/topics/etl.md>), [Temporian](<https://devfeed.tech/topics/temporian.md>)

Tags: [bigquery](<https://devfeed.tech/tags/bigquery.md>), [code](<https://devfeed.tech/tags/code.md>), [data-engineering](<https://devfeed.tech/tags/data-engineering.md>), [data-pipelines](<https://devfeed.tech/tags/data-pipelines.md>), [duckdb](<https://devfeed.tech/tags/duckdb.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [product](<https://devfeed.tech/tags/product.md>)

## AI overview

dlt's dataset interface lets teams use a consistent code path to query and process data across environments and supported engines. The article demonstrates local development with DuckDB, production deployment to warehouses such as BigQuery, and Arrow-based transfers, while noting limits around engine-specific features and tabular data.

## Source excerpt

Data engineering shouldn't require rewriting the same logic multiple times for different environments.