Posts
All the articles I've posted.
- 31 MIN READ•Aug 25, 2026
DataFusion Comet 1.0 and What Native Rust Scans Change for Spark on Iceberg
DataFusion Comet 1.0 replaces Spark Iceberg scans with native Rust. What speeds up, what still falls back to the JVM, and how to deploy it.
Apache IcebergApache SparkDataFusion Comet - 31 MIN READ•Aug 25, 2026
FSST and ALP: The Two Encodings Fixing Parquet's Weakest Compression Cases
ALP and FSST target Parquet's worst cases: floats and high-cardinality strings. How they work and what they change for Iceberg tables.
Apache ParquetencodingsALP - 33 MIN READ•Aug 25, 2026
Governance-as-Code for the Lakehouse: Managing REST Catalog RBAC and Masking in Git
Put REST catalog RBAC and masking in Git. How to review grants, apply them safely, and keep lakehouse access from drifting.
governanceREST catalogRBAC - 31 MIN READ•Aug 25, 2026
Metric Contracts in Code: Testing, Versioning, and Serving Business Logic to Multi-Agent Systems
Metric contracts in code let teams test, version, and serve business logic to multi-agent systems without each agent inventing its own SQL.
metricsAI agentssemantic layer - 31 MIN READ•Aug 25, 2026
High-Throughput Branch Merging: Automating Concurrency and Conflict Resolution in Multi-Branch Iceberg Pipelines
High-throughput Iceberg branch merges need conflict detection and automation. How to reconcile concurrent writes without stalling pipelines.
Apache Icebergbranchesconcurrency - 31 MIN READ•Aug 25, 2026
Multi-Cloud REST Catalog Topologies: Running Apache Polaris Across AWS, Azure, and GCP
Polaris can catalog Iceberg tables across AWS, Azure, and GCP. Four topologies, credential vending, and the tradeoffs of each design.
Apache PolarisREST catalogmulti-cloud - 32 MIN READ•Aug 25, 2026
Parquet-Only Manifests in Iceberg v4: Why the Metadata Layer Is Going Columnar
Iceberg v4 is moving manifests from Avro to Parquet so planners can read only the stats they need. Why the metadata layer is going columnar.
Apache IcebergIceberg v4Parquet - 31 MIN READ•Aug 25, 2026
Query Routing at Machine Scale: Dynamic Workload Distribution Across Lakehouse Engines
Route each lakehouse query by shape, not by sender. Signals, rules, and how to keep dashboards, batch jobs, and agents from sharing one engine.
query engineslakehouserouting - 31 MIN READ•Aug 25, 2026
Semantic Layer Federation: One Logical Model Over Data on Three Clouds
One logical model over Iceberg and databases on three clouds. Pushdown, egress, Reflections, and where semantic federation still breaks.
semantic layerfederationmulti-cloud - 31 MIN READ•Aug 25, 2026
Serverless Iceberg Ingestion with PyIceberg and DuckDB: Micro-Batches Without a Spark Cluster
Land small Iceberg micro-batches with PyIceberg and DuckDB in a serverless function. Commits, concurrency, and why Spark is the wrong default.
Apache IcebergPyIcebergDuckDB - 31 MIN READ•Aug 25, 2026
Zero-Copy Warehouse Modernization: Migrating Legacy Databases to Apache Iceberg Without Downtime
Move a legacy warehouse to Iceberg without downtime by virtualizing first. Consumer cutover, parity checks, and background copy without double-ETL.
Apache Icebergmigrationfederation - 35 MIN READ•Aug 24, 2026
The Agent Is Now a Named Coworker, and It Needs a File Format
Named, persistent agents need a file format. Open Agent Profile, Buzz, Grok Bot, and Hermes Bot Mode show why a portable agent identity matters.
AI agentsOpen Agent Profiledeveloper tools