Spice Cayenne – SQL acceleration built on Vortex
Hi HN, we’re Luke and Phillip, and we’re building Spice.ai OSS - a lightweight, portable data and AI engine and powered by Apache DataFusion & Ballista for SQL query, hybrid-search, and LLM-inference across disaggregated-storage used by enterprises like Barracuda Networks and Twilio. We first introduced Spice [1] on HN in 2021 and re-launched it on HN [2] in 2024 re-built from the ground up in Rust. Spice includes the concept of a Data Accelerator [3], which is a way to materialize data from disparate sources, such as other databases, in embedded databases like SQLite and DuckDB. Today we’re…
In plain words
Spice Cayenne is a lightweight, open-source data and AI engine built in Rust that accelerates SQL queries, hybrid search, and LLM inference across distributed storage systems. It uses Apache DataFusion and Ballista to materialize data from multiple sources into embedded databases like SQLite and DuckDB. The latest version introduces a new Data Accelerator based on Vortex, a columnar format designed for faster random access, scanning, and writes compared to Parquet. It is used by enterprises including Barracuda Networks and Twilio.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hi HN, we’re Luke and Phillip, and we’re building Spice.ai OSS - a lightweight, portable data and AI engine and powered by Apache DataFusion & Ballista for SQL query, hybrid-search, and LLM-inference across disaggregated-storage used by enterprises like Barracuda Networks and Twilio. We first introduced Spice [1] on HN in 2021 and re-launched it on HN [2] in 2024 re-built from the ground up in Rust. Spice includes the concept of a Data Accelerator [3], which is a way to materialize data from disparate sources, such as other databases, in embedded databases like SQLite and DuckDB. Today we’re excited to announce a new Ducklake-inspired Data Accelerator built on Vortex [3], a highly performant, extensible columnar data format that claims 100x faster random access, 10-20x faster scans, 5x faster writes with a similar compression ratio vs. Apache Parquet. In our tests with Spice, Vortex performs faster than DuckDB with a third of the memory usage, and is much more scalable (multi-file). For real-world deployments, we see the DuckDB Data Accelerator often capping out around 1TB, but Spice Cayenne can do Petabyte-scale. You can read about it at https://spice.ai/blog and in the Spice OSS release notes [4]. This is just the first version, and we’d love to get your feedback! GitHub: https://github.com/spiceai/spiceai [1] https://news.ycombinator.com/item?id=28448887 [2] https://news.ycombinator.com/item?id=39854584 [3] https://github.com/vortex-data/vortex [4] https://spiceai.org/blog/releases/v1.9.0
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