Tag: Apache Iceberg
All the articles with the tag "Apache Iceberg".
- 21 MIN READ•Aug 4, 2026
Budgeting for Agentic Analytics When Every Question Costs Something Different
Budgeting for agentic analytics when every question costs something different: token economics, query economics, instrumentation, and the cost controls that actually return.
AI AgentsTCOCost Management - 21 MIN READ•Aug 4, 2026
The Five Layers of an Agentic Lakehouse and Where the MCP Server Sits
The five layers of an agentic lakehouse and where the MCP server sits: storage, catalog, semantic layer, MCP gateway, and agent surface, plus identity, session isolation, and budgets.
AI AgentsMCPAgentic Lakehouse - 21 MIN READ•Aug 4, 2026
Autonomous Table Optimization When Your Query Workload Stops Being Predictable
Autonomous table optimization when query workloads stop being predictable: observing file layout and query patterns, scoring compaction work, adaptive sort order, and cost discipline.
Apache IcebergTable OptimizationCompaction - 21 MIN READ•Aug 4, 2026
Building Apache Iceberg Lakehouses That Run Without an Internet Connection
How to build an Apache Iceberg lakehouse that runs fully offline: storage, catalog, compute, cross-zone transfer, compliance, and the failure modes that bite.
Apache IcebergAir-GappedOn-Premises - 21 MIN READ•Aug 4, 2026
Wiring Analytical Queries to Transactional APIs in Closed-Loop Decision Agents
Wiring analytical queries to transactional APIs in closed-loop decision agents: conditional writes, sagas with compensations, decision records, and blast radius controls.
AI AgentsDecision LoopsSaga Pattern - 21 MIN READ•Aug 4, 2026
Surviving Optimistic Commit Collisions When Hundreds of Agents Write to Iceberg
Surviving optimistic commit collisions when hundreds of agents write to Iceberg: which conflicts are real, commit buffers, partitioning, and the patterns that prevent commit storms.
Apache IcebergConcurrencyOptimistic Concurrency - 21 MIN READ•Aug 4, 2026
How Iceberg V3 Deletion Vectors Fixed Merge-on-Read for Streaming Tables
How Iceberg V3 deletion vectors replaced accumulating positional delete files and made merge-on-read viable for streaming and CDC tables.
Apache IcebergIceberg V3Deletion Vectors - 21 MIN READ•Aug 4, 2026
How Iceberg V3 Variant Shredding Changed Semi-Structured Data on S3 Tables
How Iceberg V3's Variant type and Parquet shredding turn JSON columns into prunable typed columns, with real benchmark tradeoffs and a migration path.
Apache IcebergIceberg V3Variant - 21 MIN READ•Aug 4, 2026
Reading the Apache Iceberg V4 Proposals Before They Land
A field guide to the Apache Iceberg V4 proposals: adaptive metadata trees, single-file commits, typed statistics, column families, and what is safe to build on today.
Apache IcebergIceberg V4Metadata - 21 MIN READ•Aug 4, 2026
Building an Honest TCO Model for Open Lakehouses and Proprietary Warehouses
An honest TCO framework for open lakehouses versus proprietary warehouses: five cost categories, measured numbers, sensitivity analysis, and where each side still wins.
TCOData LakehouseData Warehouse - 21 MIN READ•Aug 4, 2026
Moving From Supply Chain Dashboards to Decision Loops With the Model Context Protocol
Moving from supply chain dashboards to decision loops with MCP: sense, decide, act, and verify, with typed action tools, idempotency keys, and graduated human approval.
AI AgentsMCPSupply Chain - 21 MIN READ•Aug 4, 2026
Cross-Cloud Credential Vending in Apache Polaris and the End of Permanent Storage Keys
How Apache Polaris vends short-lived, prefix-scoped storage credentials across AWS, Azure, and GCP, and how to retire permanent storage keys for good.
Apache PolarisCredential VendingSecurity