# dataloaders

Published articles for dataloaders.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Streaming datasets: 100x More Efficient

DevFeed: [Streaming datasets: 100x More Efficient](<https://devfeed.tech/articles/streaming-datasets-100x-more-efficient-7493.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/streaming-datasets>)

Author: Andres Marafioti; Quentin Lhoest; ben burtenshaw; Pedro Cuenca; merve

Published: 2025-10-27T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [datasets](<https://devfeed.tech/topics/datasets.md>), [Streaming](<https://devfeed.tech/topics/streaming.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [Caching](<https://devfeed.tech/topics/caching.md>), [Library](<https://devfeed.tech/topics/library.md>)

Tags: [caching](<https://devfeed.tech/tags/caching.md>), [dataloaders](<https://devfeed.tech/tags/dataloaders.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [developers](<https://devfeed.tech/tags/developers.md>), [hub](<https://devfeed.tech/tags/hub.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [parquet](<https://devfeed.tech/tags/parquet.md>), [performance](<https://devfeed.tech/tags/performance.md>), [s3](<https://devfeed.tech/tags/s3.md>), [scale](<https://devfeed.tech/tags/scale.md>), [storage](<https://devfeed.tech/tags/storage.md>), [streaming](<https://devfeed.tech/tags/streaming.md>), [xet](<https://devfeed.tech/tags/xet.md>)

### AI overview

The article presents major improvements to streaming datasets at terabyte scale, allowing training to begin without downloading data locally. The changes reduce startup requests by up to 100x, resolve data files 10x faster, double streaming speed, and improve efficiency for highly concurrent workers.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Handling the N+1 Problem Declaratively with Apollo Connectors

DevFeed: [Handling the N+1 Problem Declaratively with Apollo Connectors](<https://devfeed.tech/articles/handling-the-n-1-problem-declaratively-with-apollo-connectors-23354.md>)

Original publisher: [Read original article](<https://www.apollographql.com/blog/handling-the-n1-problem-declaratively-with-apollo-connectors>)

Author: Lenny Burdette

Published: 2025-06-24T08:53:29Z

Content type: tutorial

Language: en

Sources: [Apollo Blog](<https://devfeed.tech/sources/apollo-blog.md>)

Topics: [Apollo Connectors](<https://devfeed.tech/topics/apollo-connectors.md>), [GraphQL](<https://devfeed.tech/topics/graphql.md>), [dataloaders](<https://devfeed.tech/topics/dataloaders.md>), [API](<https://devfeed.tech/topics/api.md>)

Tags: [apollo-connectors](<https://devfeed.tech/tags/apollo-connectors.md>), [batching](<https://devfeed.tech/tags/batching.md>), [connectors](<https://devfeed.tech/tags/connectors.md>), [dataloaders](<https://devfeed.tech/tags/dataloaders.md>), [graphql](<https://devfeed.tech/tags/graphql.md>), [performance](<https://devfeed.tech/tags/performance.md>)

### AI overview

This tutorial explains how Apollo Connectors can address the N+1 query problem declaratively with Apollo Router 2.3 and Federation 2.11. It introduces the problem, compares the approach with DataLoaders, and describes how batching, scheduling, deduplication, and entity association work in Connectors.

### Source excerpt

With the release of Apollo Router 2.3 and Federation 2.11, Apollo Connectors can now avoid the dreaded N+1 query problem! You can make your API faster and more efficient by changing your Connectors to use the variable instead of the variable. If you want to learn more about the N+1 problem and how Connectors batching works internally, please read on! The N+1 query problem is a classic performance killer that sneaks up on developers.