Tagged articles

Zero ETL

4 articles · Page 1 of 1

Jun 19, 2026 · Big Data

Why Real-Time Data Lake Ingestion Is Dropping ETL in the AI Era: Architecture Simplification from Kafka to Iceberg

In the AI‑driven era, enterprises need a data foundation that supports both real‑time consumption and long‑term historical analysis, and the emerging "zero‑ETL" trend moves generic ingestion capabilities from external Flink/Spark jobs into a streamlined Kafka‑to‑Iceberg pipeline, reducing complexity while preserving low latency, consistency, schema evolution, CDC semantics and open‑ecosystem compatibility.

Data LakeIcebergKafka

0 likes · 25 min read

Why Real-Time Data Lake Ingestion Is Dropping ETL in the AI Era: Architecture Simplification from Kafka to Iceberg

Alibaba Cloud Developer

Jun 18, 2026 · Big Data

How AI-Driven Real-Time Data Lakes Are Ditching ETL: A Kafka‑to‑Iceberg Architecture Simplification

In the AI era, enterprises need a data foundation that supports both low‑latency streaming and long‑term analytics, and the combination of Kafka, Iceberg and object storage is emerging as a preferred solution; by moving ingestion capabilities closer to the message layer and eliminating external ETL jobs, a "zero‑ETL" approach reduces architectural complexity, improves consistency, and streamlines schema evolution and small‑file management.

Data LakeIcebergKafka

0 likes · 27 min read

How AI-Driven Real-Time Data Lakes Are Ditching ETL: A Kafka‑to‑Iceberg Architecture Simplification

AI Waka

Jun 8, 2026 · Artificial Intelligence

Building Reliable Snowflake AI Agents: SKILL‑Based SOPs for Production Analytics

The article explains how Snowflake’s AI agents can achieve production‑grade reliability by encoding standard operating procedures as version‑controlled, declarative SKILL contracts that enforce deterministic logic, validation, guardrails, and progressive disclosure, supported by a GitOps‑driven zero‑ETL deployment pipeline.

AI AgentCortex SearchGitOps

0 likes · 14 min read

Building Reliable Snowflake AI Agents: SKILL‑Based SOPs for Production Analytics

Alibaba Cloud Native

Apr 2, 2026 · Industry Insights

How EventHouse Redefines AI‑Native Event Data Platforms for the Agent Era

EventHouse, Alibaba Cloud’s AI‑native data platform, unifies event ingestion, storage, governance and intelligent analysis through a layered architecture that supports real‑time SQL, zero‑ETL federation and Luma Agent‑driven conversational analytics, positioning it as a next‑generation AI data foundation for enterprises seeking to turn event streams into actionable insights.

AI Data PlatformAgentic AICloud Native

0 likes · 16 min read

How EventHouse Redefines AI‑Native Event Data Platforms for the Agent Era