Tag:Apache Iceberg

Articles tagged "Apache Iceberg".

• 31 MIN READ•Sep 28, 2026

  Keeping Audit Snapshots Alive While Iceberg Snapshot Expiration Runs Every Night

  How Iceberg snapshot tags keep audit snapshots alive through nightly expiration: retention calendars, RETAIN semantics, compaction cost, and erasure conflicts.

  Apache IcebergSnapshot ExpirationData Governance
• 31 MIN READ•Sep 21, 2026

  Why the Iceberg DataFusion Integration Is Moving to Apache DataFusion

  Why the Iceberg DataFusion integration moved to the DataFusion project, and what the split means for users, Comet, and iceberg-rust contributors.

  Apache DataFusionApache IcebergRust
• 32 MIN READ•Sep 21, 2026

  What Iceberg v4's Proposed FILE Type Means for Multimodal Tables

  Iceberg v4's proposed FILE type brings first-class media references to tables, via Parquet's FILE logical type, ranges, checksums, and pre-signed URLs.

  Apache IcebergIceberg v4Multimodal
• 39 MIN READ•Sep 21, 2026

  Fast Classification Models, LLMs, and the Apache Iceberg Lakehouse

  How fast classification models like Jev alongside open alternatives such as GLiClass compare with LLMs, and how to run both together inside an Apache Iceberg lakehouse.

  Apache IcebergAILLM
• 31 MIN READ•Sep 21, 2026

  Parquet Page Indexes and the Last Mile of Pruning in Apache Iceberg

  Parquet page indexes can cut selective Iceberg scans by an order of magnitude on sorted data. How they work, what they cost, and how to lay out tables.

  Apache ParquetApache IcebergPruning
• 31 MIN READ•Sep 21, 2026

  Vector Search Directly Over Iceberg Tables, and When You Still Need a Vector Database

  Embeddings are just columns. When exact vector search over Iceberg scans beats a vector database, when it does not, and how to lay out tables.

  Vector SearchApache IcebergRAG
• 31 MIN READ•Sep 10, 2026

  Running Apache Polaris in Production

  Apache Polaris past the quickstart: persistence backends, realm bootstrap, replica token signing, upgrades, backups, and which failures take the lakehouse offline.

  Apache PolarisApache Icebergcatalogs
• 31 MIN READ•Sep 10, 2026

  What the 2026 Consolidation Means for Open Formats

  Tabular, Dremio, and a wave of data platform acquisitions: what changes for teams building on open formats and which guarantees survive a change of ownership.

  open formatsacquisitionsdata platform consolidation
• 31 MIN READ•Sep 10, 2026

  Migrating Into Iceberg Without Moving Data

  add_files, snapshot, and migrate compared: the three in-place paths into Iceberg, the reconciliation each requires, the layout traps, and the rollback story.

  Apache Icebergmigrationmetadata
• 31 MIN READ•Sep 10, 2026

  What Iceberg Table Maintenance Actually Costs

  A cost model for compaction, snapshot expiry, orphan cleanup, and manifest rewriting: what each operation spends, on which meter, and how to set a schedule.

  Apache Icebergtable maintenancecompaction
• 30 MIN READ•Sep 10, 2026

  Running an Iceberg Lakehouse on Kubernetes

  Catalog, maintenance, and compaction as Kubernetes workloads: scheduling classes, job structure, credential flow, and the failures that come from the interaction.

  KubernetesApache IcebergApache Polaris
• 31 MIN READ•Sep 10, 2026

  Partition Statistics Files in Apache Iceberg

  The underused Iceberg metadata for planning: what the partition statistics file holds, what the spec guarantees, how to write one, and when it earns its slot.

  Apache Icebergquery planningmetadata