Is Parquet becoming the bottleneck? Why new storage formats are emerging in 2025 (Lance, Vortex, and more)

Parquet gave data lakes a common language: columnar layout, good compression, and fast scans. That still works well for classic analytics. But workloads have changed. We now mix wide scans with point lookups, handle embeddings and images, and run on S3-first stacks. On NVMe you want lots of tiny random reads. On S3 you want fewer, larger range requests. A format tuned for one world can feel chatty or slow in the other.

Why We Built Our Own SQL Parser From Scratch: A Rust Implementation Story

The story of why Databend chose to build its own SQL parser, the challenges faced, and how Rust's type system guided the solution.

Bluesky

Bluesky

Bluesky

Bluesky

Analyzing Hugging Face Datasets with Databend

Directly query Hugging Face datasets through Databend to simplify your data science workflow.

Introduction