Real-Time Agentic Analytics with ClickHouse
ClickHouse has become the leading real-time analytics engine for AI agent workloads, with event-loop architectures that let agents query and act.
The archive
Writing, page 25
652 posts on Apache Iceberg, lakehouse architecture, data engineering and applied AI.
Composable Analytics Beats Metric Catalogs
Metric catalogs define what terms mean. Composable analytics defines how terms combine, transform, and relate.
Goal-Directed Analytics Agents on Apache Iceberg
How goal-directed analytics agents decompose business questions into sub-tasks, execute action loops over Apache Iceberg tables, and use the lakehouse.
Iceberg Remote Signing for Regulated Datasets
Iceberg REST catalog remote signing provides per-file pre-signed URL access for regulated datasets.
Apache Iceberg v3 Deletion Vectors on Snowflake
Apache Iceberg v3 deletion vectors replace positional delete files with binary bitmaps in Puffin files, delivering up to 10x faster DML on Snowflake.
CDC Without Complexity Using Iceberg v3 Row Lineage
Iceberg v3 row lineage adds _row_id and _last_updated_sequence_number to every table, enabling native change data capture without Debezium or Kafka.
The 2026 Guide to Iceberg View Federation
Iceberg views standardize SQL view definitions across engines, enabling view federation across Polaris, Nessie, and Gravitino catalogs.
Implementing MCP in the Lakehouse
How to build a Model Context Protocol (MCP) server that exposes lakehouse tables and semantic views as AI-accessible tools, with Python implementation.
Microsoft Fabric Build 2026 Agentic Analytics Stack
Microsoft Build 2026 revealed an agentic analytics stack built on Fabric IQ, OneLake Iceberg support, and semantic models.
Modern Python Tooling for Apache Iceberg
PyIceberg, IceFrame, and the Iceberg CLI form a complete Python toolchain for Iceberg table management.