Welcome to the Daft blog
Join us as we explore innovative ways to handle multimodal datasets, optimize performance, and simplify your data workflows.
Eventual Raises $30M to Build the Future of Data
How to Build Scalable, End-to-end Batch Inference Pipelines with Daft
From prompts to parquet: making batch inference simple, fast, and scalable.
24 Trillion Tokens, 0 Crashes
How Essential AI Built Essential-Web v1.0 with Daft
Embedding Millions of Text Documents With Qwen3
Near-100% GPU Utilization
Processing 300K Images Without OOM
A Streaming Solution
Multimodal Data Processing Goes Global
Launching Daft Chinese Community in partnership with Bytedance
We cloned over 15,000 repos to find the best developers
An adventure in AI and data engineering to analyze developers across Github
DeepSeek smallpond, 3FS and data processing for AI
A closer look beyond the AI hype
From v0.2 to v0.3: Harder, Better, Faster, Stronger
Join us on the journey from Daft v0.2 to v0.3!
Introducing Daft-SQL
A SQL API enabling users to interact with their data in a new but familiar way!
Reading Delta Lake with Daft
Announcing the launch of Daft's Delta Lake read support
Adversarial file reading: from 10,000 small CSVs to massive Parquet files
How Daft optimizes the reading of real-world data which is often a mix of "many small files" and "few large files"
Announcing Daft 0.2: 10x faster IO from S3
Reading data from S3 just got 10x faster!
