Wang Zhiwu, a big data expert, dedicated to sharing big data technology.
This article summarizes how the Doris‑Paimon lakehouse architecture leverages Doris' high‑performance OLAP engine to accelerate lake queries, provides a unified data analysis gateway, supports unified data integration, and enables open, layered data modeling for modern big‑data workloads.
This article introduces the concept of AI-powered Data Agents, outlines their key features and use cases across enterprise analytics, data governance, and intelligent customer service, and reviews recent implementations from Google, Alibaba Cloud, and ByteDance, highlighting their impact on modern data-driven workflows.
This article explains the Model Context Protocol (MCP) as a standard for LLM‑data integration, describes Retrieval‑Augmented Generation (RAG) techniques to reduce hallucinations, and introduces vector databases like Milvus that store high‑dimensional embeddings for efficient AI retrieval tasks.
This article analyzes why Elasticsearch struggles with large‑scale, complex real‑time analytics and demonstrates how Apache Doris’s MPP, columnar storage, and native SQL support provide a cost‑effective, high‑performance alternative, illustrated with detailed enterprise case studies.
Apache Kafka 4.0 introduces a groundbreaking KRaft architecture that removes ZooKeeper, a revamped consumer‑group protocol that dramatically speeds up rebalancing, a new queue mode for point‑to‑point messaging, upgraded Java requirements, streamlined APIs, and numerous performance and security enhancements, reshaping both development and operations for large‑scale streaming workloads.
This article reviews how major tech firms such as Alibaba, Tencent, ByteDance, and Kuaishou tackled lakehouse challenges—including architecture fragmentation, cost, scalability, and complex multimodal data—by adopting real‑time lakehouse solutions like Flink + Paimon, Iceberg + StarRocks, Hudi + LAS, and Doris + Alluxio, and outlines the resulting performance and cost gains.
The article analyzes how the rapid rise of open‑source large‑model AI in 2025 is reshaping the data development profession, urging developers to transition from specialized data‑engineer roles to full‑stack AI data engineering skills such as distributed computing, lake‑house architectures, and model tuning.
An overview of Paimon 1.0’s milestone improvements, focusing on the optimized local Lookup performance, the new sort‑lookup‑store based PFile key‑value format, its four‑part structure, and detailed write and read procedures that enhance large‑scale dimension table joins.
The article discusses how large language model tools such as Cursor, DeepSeek, and Doubao are increasingly assisting code writing, SQL translation, job‑failure analysis, and documentation in data‑development workflows, while also reshaping job requirements and creating new opportunities for skilled developers.
This article presents a detailed overview of Douyin Group's Data Asset Management Platform, focusing on the evolution, architecture, modeling, metrics, and application scenarios of its large‑scale data lineage system, and outlines future directions for full‑coverage, fine‑grained lineage capabilities.
