Three lakehouse stacks for adding AI/ML and streaming on top of an existing warehouse, compared through a FinOps lens: DBUs, DPUs, TB-scanned, S3 GB-month, and egress, walked through real workload patterns with 2026 prices.
Lance is a columnar storage format built for machine learning workloads — fast random access, native vector indexing, and zero-copy Arrow integration. This article walks through the format itself, how LanceDB builds on top of it, and how I wired it into a live NATS stream to build a simple semantic search layer over real-time events.
Most ML pipeline failures are not exotic model bugs — they are data issues that nobody encoded as checks. This article walks through building guardrails using pandas, Apache DataFusion, data contracts, and the Arrow C Data Interface.
Two Rust projects, one conceptual divide. Ares fetches arbitrary web pages and uses LLMs to extract structured data; Ceres harvests metadata from CKAN portals and indexes it semantically. Together they show what it looks like to move from scraping scripts to production data pipelines.
A deep dive into Mosaico, the robotics data platform written in Rust: client-server architecture, semantic ontologies, data-oriented debugging, my journey within it, and the integration with Data Contract Engine.
Ceres is a semantic search engine for CKAN portals. Built in Rust with Tokio and PostgreSQL+pgvector, it bridges the gap between how people search and how public administrations name their datasets.
Polars completes the Rust data engineering ecosystem: lazy evaluation, Apache Arrow, and native Iceberg V3 integration for performant analytics that compete with distributed clusters. The third pillar of the RisingWave + Lakekeeper + Polars stack.
An exploration of Lakekeeper, the Iceberg REST catalog in Rust that completes the data engineering ecosystem: enterprise security with vended credentials, multi-tenancy, and RisingWave integration to build streaming lakehouses without JVM
The partnership between RisingWave and Iceberg-Rust represents a window into where modern data engineering is heading: real-time CDC streaming, intelligent hybrid delete strategy, and a performant Rust ecosystem challenging JVM dominance.