Welcome to the Daft blog
Join us as we explore innovative ways to handle multimodal datasets, optimize performance, and simplify your data workflows.
How to Build Scalable, End-to-end Batch Inference Pipelines with Daft
Daft makes it easy to express these pipelines end-to-end, while seamlessly scaling them up to handle massive workloads.
Embedding Millions of Text Documents With Qwen3
Learn how to achieve near-100% GPU utilization processing millions of text documents with Qwen3 embeddings.
Processing 300K Images Without OOM
A Streaming Solution
We cloned over 15,000 repos to find the best developers
An adventure in AI and data engineering to analyze developers across Github
High-Performance File System Support With DeepSeek 3FS
Learn how Daft integrates with DeepSeek SmallPond 3FS to deliver faster file access and efficient data handling for modern workloads.
Introducing Daft-SQL for High-Performance Data Exploration
A SQL API enabling users to interact with their data in a new but familiar way. Learn how Daft-SQL brings fast, scalable querying to multimodal workloads, helping teams explore large datasets efficiently with a distributed engine.
Reading Delta Lake with Daft
Discover how Daft reads Delta Lake tables efficiently, giving teams fast access to large datasets and seamless integration into data workflows.
Adversarial file reading: from 10,000 small CSVs to massive Parquet files
Learn how adversarial file reading speeds up data ingestion at scale, enabling fast conversion from thousands of CSVs into efficient Parquet files.
Working with the Apache Parquet file format
This guide shows how Apache Parquet boosts read performance, lowers storage use, and supports efficient workflows for large analytical datasets.
