Topic
lakehouse
36 posts tagged “lakehouse”.
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Your Data Agents Are CPU-Bound, and the Hardware Market Just Noticed
Analytics agents spend most of their time on CPU-bound tool calls, not the model. Size three planes separately and measure your ratio from traces.
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How Apache Polaris Plans to Share Iceberg Tables Across Organizations
Apache Polaris's Open Sharing proposal adds first-class shares, external consumers, and listings so any Iceberg REST engine can read shared tables.
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What a Query Costs
Four meters, their real proportions, and how to attribute compute to a query, a table, and a team so a platform can answer what a dashboard costs to run.
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Postgres Meets the Lakehouse: pg_lake, pg_duckdb, and When Postgres Is Enough
What pg_lake, pg_duckdb, and pg_mooncake do at the Iceberg level, and honest thresholds for when Postgres is enough.
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Synthetic Data in the Lakehouse: Generation, Governance, and Testing
What synthetic data in a lakehouse is for, the generation methods, how to preserve fidelity, and where synthetic tables belong.
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Securing the Agentic Lakehouse Gateway: Preventing Prompt Injection and Data Exfiltration
Agentic lakehouse gateways face prompt injection and exfiltration through query results. A threat model and defenses for the layer in front of data.
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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.
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Defending the Lakehouse Gateway Against Prompt Injection and Data Exfiltration
Defending the lakehouse gateway against prompt injection and data exfiltration: per-user identity, no-SQL tool surfaces, volume bounds, and detection.
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Designing Batch Pipelines That Write Well Into Apache Iceberg
How to design batch pipelines that write well into Apache Iceberg: commit strategy, partitioning, sort order, write-audit-publish, and maintenance done right.
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Federating Oracle With an Open Lakehouse Instead of Migrating It
Federate first so analytics work now, migrate what benefits from migrating, and leave the rest where it is indefinitely.
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The Apache Iceberg Market in the Middle of 2026
A survey of the Apache Iceberg market in July 2026: the state of the specification, platform support, the acquisition wave, the catalog contest, and how.
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The Whole Lakehouse Fits on Your Laptop Now
Consumer hardware, columnar formats, single-node engines, and the Iceberg REST catalog crossed a threshold: a large share of cluster work now runs locally.
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Iceberg's Next Version Depends on Decisions Being Made in Parquet
The Iceberg and Parquet specifications are co-evolving. Several of the most consequential Iceberg v4 proposals are waiting on Parquet work.
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Building a Lakehouse That Stays Inside the Border
Residency is a storage location. Sovereignty is who can compel access, who operates the systems, and whether you can leave.
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Table Maintenance Stopped Being a Product
Iceberg table maintenance commoditized when every platform started shipping it. What the six operations are, what they cost, and the observability you.
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Three Vendors Are Rebuilding the Path From Transaction to Agent
Databricks, Snowflake, and SAP are closing the gap between operational databases and analytical platforms through acquisition, betting on different layers.
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Data Lakehouse Open Standards for AI Agents
An in-depth exploration of data lakehouse open standards for ai agents
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Dremio Lakehouse AI Report: Agentic Lessons
An in-depth exploration of dremio lakehouse ai report: agentic lessons
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Zero-Copy Mirroring to Open Iceberg Tables
An in-depth exploration of zero-copy mirroring to open iceberg tables
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Migrating Proprietary Warehouses to Open Lakehouses: The 2026 Playbook for Zero-Copy Metadata Translation
Every warehouse migration sounds simpler before the first inventory. Then the team discovers old dashboards, hidden dependencies, undocumented stor...
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Lakehouse as the Operating Layer for Agentic AI
Agentic AI announcements are useful when they validate the need for governed data, semantic context, and cost-aware execution.
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What Is LTAP in the Lakehouse?
Lakehouse transactional analytical processing is useful only when teams define freshness, isolation, and workload boundaries clearly.
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Agentic Lakehouse Concurrency and Isolation
How Iceberg optimistic concurrency control, partition-level isolation, and idempotency keys enable safe concurrent writes from multiple AI agents.
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Anatomy of an Agentic Lakehouse
The four-layer architecture of the agentic lakehouse: object storage, Apache Iceberg table format, Apache Polaris catalog, and the semantic/agent layer.
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Lakehouse Context Layers with Atlan and Iceberg v3
Lakehouse context layers bridge the gap between raw Iceberg tables and AI agents that need business meaning.
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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.
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Iceberg Remote Signing for Regulated Datasets
Iceberg REST catalog remote signing provides per-file pre-signed URL access for regulated datasets.
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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.
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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.
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The 2026 Guide to Iceberg View Federation
Iceberg views standardize SQL view definitions across engines, enabling view federation across Polaris, Nessie, and Gravitino catalogs.
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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.
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Modern Python Tooling for Apache Iceberg
PyIceberg, IceFrame, and the Iceberg CLI form a complete Python toolchain for Iceberg table management.
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REST Catalog Credential Vending for Lakehouse Security
Iceberg REST catalog credential vending issues short-lived, table-scoped storage tokens for S3, ADLS, and GCS.
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Securing Agent Identities in the Lakehouse
How OAuth 2. 0 token exchange, OAuth 2. 1 device authorization grant, credential vending, and fine-grained access control secure AI agent identities.
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Bidirectional Iceberg Writes with Horizon Catalog
Snowflake Horizon Catalog enables bidirectional Iceberg writes from external engines like Spark and Trino, powered by Apache Polaris.
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Zero-Copy Mirroring for Modern Lakehouse Migration
Zero-copy mirroring gives teams a safer migration path because they can expose a lakehouse surface before they duplicate every byte or rewrite every workload.