The Future of Manufacturing Data Intelligence 製造業資料智慧的未來
LongDB is an AI-ready lakehouse platform that unifies data lakes and data warehouses, enabling enterprises to harness the full potential of their data for analytics, AI/ML, and real-time decision making—designed specifically for semiconductor and high-end manufacturing.
LongDB 是一個 AI 就緒的湖倉一體平台,融合資料湖與資料倉儲的優勢,助力企業充分釋放資料價值,實現高效分析、AI/ML 應用與即時決策——專為半導體和高階製造業打造。
The Data Silo Problem in Manufacturing製造業的資料孤島問題
Modern manufacturing enterprises accumulate multiple analytics platforms over time. Each system may have been right for its specific use case, but the aggregate result is fragmented data that limits AI/ML adoption.
現代製造企業隨著時間推移累積了多個分析平台。每個系統可能適合其特定用例,但整體結果是資料碎片化,阻礙了 AI/ML 的落地應用。
Fragmented Analytics分析系統碎片化
"Oracle is slow, add an MPP data warehouse for analytics" — each application maintains its own data copy. Same KPI shows different values in different systems.
"Oracle 太慢,加個 GP/Vertica 做分析"——每個應用都維護自己的資料副本,同一 KPI 在不同系統中顯示不同值。
High TCO & Complexity高成本與複雜性
Multiple licenses, multiple support contracts. 30-40% of IT resources consumed by data sync and integration pipelines in fragmented architectures.
多個授權證,多份支援合同。在碎片化架構中,30-40% 的 IT 資源消耗在資料同步和整合管線上。
Slow Time-to-Insight洞察時間過長
Dashboard data may be hours or days old. Data scientists spend 60-80% of time on data preparation instead of building models.
儀表板資料可能是數小時或數天前的。資料科學家花费 60-80% 的時間在資料準備上,而不是建構模型。
AI/ML Adoption BarriersAI/ML 落地困難
AI initiatives blocked by scattered, inconsistent data. Feature engineering requires access to multiple disconnected systems.
AI 專案被分散、不一致的資料阻礙。特徵工程需要存取多個斷開連結的系統。
LongDB: Unified Lakehouse PlatformLongDB:統一的湖倉一體平台
A single platform that combines the best of data warehouses and data lakes, purpose-built for modern AI workloads in manufacturing environments.
一個融合資料倉儲和資料湖優勢的統一平台,專為製造業現代 AI 工作負載量身打造。
Lakehouse Architecture湖倉一體架構
Unified storage for structured, semi-structured, and unstructured data with full ACID transactions and schema evolution. Virtual Table mechanism supports flexible and extensible storage options.
統一儲存結構化、半結構化和非結構化資料,具備完整的 ACID 事务和 Schema 演進能力。虛擬表機制支援靈活可擴展的儲存選項。
AI-Native DesignAI 原生設計
Built-in ML runtime, feature store, model registry, and SupraBrain AI engine for seamless integration of AI/ML workloads with your data.
內建 ML 執行時、特徵儲存、模型註冊表和 SupraBrain AI 引擎,實現 AI/ML 工作負載與資料的無縫整合。
Hybrid Cloud Ready混合雲就緒
Deploy on-premises, private cloud, or public cloud. Full data sovereignty with seamless migration and consistent APIs across environments.
支援地端部署、私有雲或公有雲。完全資料主权,無縫遷移,跨環境一致的 API。
Real-time + Batch Unified即時+批處理統一
Single SQL interface for BI, reporting, streaming analytics, and ad-hoc queries. No data movement between systems required.
單一 SQL 接口支援 BI、報表、流式分析和即席查詢。無需在系統間移動資料。
Two Powerful Products, One Vision兩大產品,一個願景
LongDB PlatformLongDB 平台
The core lakehouse platform providing unified data storage, processing, and analytics capabilities for enterprise-scale manufacturing workloads.
核心湖倉一體平台,為企業級製造業工作負載提供統一的資料儲存、處理和分析能力。
- Unified lakehouse with ACID transactions
- Time travel & schema evolution capability
- Real-time streaming ingestion (Kafka, CDC)
- Virtual Table for extensible storage options
- Data Science Studio for notebooks & ML
- Enterprise security, governance & lineage
- 統一湖倉,支援 ACID 事务
- 時間旅行與 Schema 演進能力
- 即時流式攝入(Kafka、CDC)
- 虛擬表機制支援可擴展儲存選項
- 資料科學工作室(Notebook 與 ML)
- 企業級安全、治理與血緣追踪
SupraBrain AI EngineSupraBrain AI 引擎
Next-generation agentic AI engine that brings intelligent automation and natural language interfaces to your data operations.
新一代智慧代理 AI 引擎,為資料操作帶來智慧自動化和自然語言交互能力。
- Natural language to SQL generation
- Autonomous data agents with reasoning
- Intelligent query optimization
- Automated insight discovery & alerting
- Multi-modal data analysis (images, docs)
- Enterprise model integration (GPT, Claude, Gemini, Qwen, DeepSeek)
- 自然語言轉 SQL 生成
- 具備推理能力的自主資料智慧代理
- 智慧查詢最佳化
- 自動洞察發現與告警
- 多模态資料分析(影像、文件)
- 企業級模型整合(GPT、Claude、Gemini、Qwen、DeepSeek)
🏭 Production Deployments生產環境部署案例
LongDB has production deployments in semiconductor and high-end manufacturing enterprises:
LongDB 已在半導體和高階製造企業中投入生產使用:
Client names available under NDA. Reference calls can be arranged during evaluation.
客戶名稱可在簽署保密協議后提供。評估期間可安排参考客戶溝通。
Unified Data + AI Platform for Manufacturing面向製造業的統一資料+AI平台
LongDB Platform is an enterprise-grade lakehouse that unifies data management, analytics, and AI capabilities in a single, coherent platform designed for semiconductor and high-end manufacturing.
LongDB 平台是企業級湖倉一體系統,將資料管理、分析和 AI 能力統一在一個為半導體和高階製造業設計的一致性平台中。
Enterprise-Grade Features企業級功能
Unified Lakehouse Storage統一湖倉儲存
Native storage engine with ACID transactions, time travel, and schema evolution. Virtual Table mechanism supports flexible and extensible storage options.
原生儲存引擎,支援 ACID 事务、時間旅行和 Schema 演進。虛擬表機制支援靈活可擴展的儲存選項。
Real-time Streaming即時流處理
Kafka Connect, CDC, Spark Streaming, and Bulk Loaders for ingesting millions of events per second with exactly-once semantics.
Kafka Connect、CDC、Spark Streaming 和批次載入器,每秒攝入數百萬事件,支援精确一次語意。
Data Governance資料治理
Built-in data catalog, lineage tracking, access control (RBAC), data quality monitoring, and audit logging.
內建資料目錄、血緣追踪、存取控制(RBAC)、資料品質監控和稽核日誌。
Agile BI敏捷 BI
Interactive dashboards, drag-and-drop visualization builder, and self-service analytics for business users.
交互式儀表板、拖拽式視覺化建構器,為業務用户提供自助分析能力。
Data Science Studio資料科學工作室
Jupyter-compatible notebooks with support for Python, R, Scala, and SQL. Integrated with feature store and model registry.
兼容 Jupyter 的筆記本,支援 Python、R、Scala 和 SQL。與特徵儲存和模型註冊表整合。
ML IntegrationML 整合
Native ML runtime, feature store, model registry, and MLflow integration. Train and deploy models directly on platform data.
原生 ML 執行時、特徵儲存、模型註冊表和 MLflow 整合。直接在平台資料上訓練和部署模型。
SupraBrain AI
An enterprise-grade agentic AI engine built on four core pillars: conversational interface, RAG-powered knowledge, context-aware data agents, and extensible plugin architecture. SupraBrain transforms how organizations interact with and extract value from their data.
企業級智慧代理 AI 引擎,基于四大核心支柱:對話式界面、RAG 驅動的知識庫、上下文感知的資料智慧代理和可擴展的外掛架構。SupraBrain 重新定義企業與資料的交互方式,釋放資料價值。
Four Pillars of Intelligent Data Interaction智慧資料交互的四大支柱
SupraBrain combines conversational AI, retrieval-augmented generation, domain-aware data agents, and a flexible plugin ecosystem into a unified agentic engine.
SupraBrain 將對話式 AI、檢索增强生成、領域感知資料智慧代理和靈活的外掛生態系統融合為統一的智慧代理引擎。
1. Conversational Interface1. 對話式界面
ChatGPT-style InteractionChatGPT 式交互
Intuitive chat interface for natural language queries in English, Chinese, and other languages. Ask questions, get answers, visualizations, and actionable insights without writing code. Maintains conversation context for follow-up questions and iterative exploration.
直观的聊天界面,支援中英文等多語言自然語言查詢。無需編寫代码即可提問、獲取答案、視覺化和可操作洞察。保持對話上下文,支援後續問題和迭代探索。
2. RAG Knowledge Base2. RAG 知識庫
Retrieval-Augmented Generation檢索增强生成
Enterprise knowledge base powered by RAG technology. Ingest documents, manuals, SOPs, and domain knowledge to provide accurate, context-aware responses. Vector embeddings enable semantic search across unstructured content with real-time retrieval.
由 RAG 技术驅動的企業知識庫。攝入文件、手册、SOP 和領域知識,提供準確、上下文感知的回應。向量嵌入支援非結構化内容的語意搜尋和即時檢索。
3. Data Agent3. 資料智慧代理
Context & Domain Model Awareness上下文與領域模型感知
Intelligent data agent that deeply understands your data context, schema relationships, and domain-specific data models. Automatically generates accurate SQL, performs multi-step reasoning, and executes complex analytical workflows with full data lineage awareness.
智慧資料代理深度理解資料上下文、Schema 關係和領域特定資料模型。自動生成準確的 SQL,執行多步推理,在完整資料血緣感知下執行複雜分析工作流。
4. Plugin/MCP Architecture4. 外掛/MCP 架構
Extensibility & Integration可擴展性與整合
Open plugin architecture based on Model Context Protocol (MCP) for seamless extensibility. Connect to external tools, APIs, and enterprise systems. Build custom capabilities while maintaining security and governance controls across all integrations.
基于模型上下文協議(MCP)的開放外掛架構,實現無縫擴展。連結外部工具、API 和企業系統。建構自訂能力,同時在所有整合中保持安全和治理控制。
Intelligence at Every Layer全層智慧
Intelligent Query Optimization智慧查詢最佳化
AI-powered query analysis that suggests indexes, rewrites inefficient queries, and automatically tunes performance.
AI 驅動的查詢分析,建議索引,重寫低效查詢,自動調優性能。
Automated Insight Discovery自動洞察發現
Proactively surfaces anomalies, trends, and patterns in your data. Get alerted to important changes before they become problems.
主動發現資料中的異常、趨勢和模式。在問題發生前获得重要變化的警報。
Multi-modal Analysis多模态分析
Analyze images, documents, and sensor data alongside structured data. Perfect for manufacturing quality control.
結合結構化資料分析影像、文件和感測器資料。非常適合製造業品質控制。
SupraBrain in ActionSupraBrain 實戰案例
🎯 Self-Service Analytics自助分析
"Show me yield by equipment for last month, compared to target, and highlight any equipment below 95%"
"顯示上個月按設備劃分的良率,與目標比較,並醒目標示顯示低于 95% 的設備"
→ Generates SQL, creates visualization, adds commentary→ 生成 SQL,建立視覺化,添加註解
🔍 Root Cause Analysis根因分析
"Why did our yield rate drop on production line 3 last Tuesday afternoon?"
"為什麼上周二下午 3 號生產線的良率下降了?"
→ Correlates sensor data, identifies anomalies, suggests causes→ 關聯感測器資料,辨識異常,建議原因
📊 Report Automation報表自動化
"Generate a weekly executive summary of key manufacturing metrics and email it every Monday"
"生成關鍵製造指標的每周高管摘要,每周一通過郵件發送"
→ Creates automated pipeline, schedules delivery→ 建立自動化管線,排程交付
🤖 Predictive Maintenance預測性維護
"Alert me when any equipment shows signs of potential failure in the next 48 hours"
"當任何設備在未來 48 小時内顯示潜在故障跡象時提醒我"
→ Deploys ML model, sets up real-time monitoring→ 部署 ML 模型,設定即時監控
🧠 LLM IntegrationLLM 整合
SupraBrain supports multiple model providers including GPT, Claude, Gemini, Qwen, and DeepSeek. Organizations can use cloud-hosted models or deploy on-premises LLM/LVM/VLM/ML models for full data privacy. Custom fine-tuning available for domain-specific terminology.
SupraBrain 支援多种模型供應商,包括 GPT、Claude、Gemini、Qwen 和 DeepSeek。企業可以使用雲代管模型或地端部署 LLM/LVM/VLM/ML 模型以確保資料隱私。支援针對領域特定術語的自訂微調。
Lakehouse Architecture Explained湖倉架構詳解
LongDB combines the best of data warehouses (reliability, governance, performance) with data lakes (flexibility, scale, cost) in a single unified architecture.
LongDB 將資料倉儲的優勢(可靠性、治理、性能)與資料湖的優勢(靈活性、規模、成本)融合在單一統一架構中。
Flexible Hybrid Cloud Architecture靈活的混合雲架構
On-Premises地端部署
Full data sovereignty and compliance with air-gap requirements. Leverage existing infrastructure.
完全資料主权,符合物理隔離要求。充分利用現有基礎設施。
- Complete data control
- Air-gap compatible
- Custom hardware optimization
- 完全資料控制
- 物理隔離兼容
- 自訂硬件最佳化
Private Cloud私有雲
Run on VMware, OpenStack, or Kubernetes with cloud-like elasticity while maintaining isolation.
在 VMware、OpenStack 或 Kubernetes 上執行,享受類似雲的彈性,同時保持隔離。
- Elastic scaling
- Network isolation
- Existing infra integration
- 彈性擴展
- 網路隔離
- 現有基礎設施整合
Public Cloud公有雲
Deploy on AWS, Azure, GCP, Alibaba Cloud, Huawei Cloud, or Tencent Cloud. Take advantage of managed services and global scale.
部署在 AWS、Azure、GCP、阿里雲、華為雲或騰訊雲上。利用代管服務和全球規模。
- Managed infrastructure
- Global availability
- Pay-as-you-go pricing
- 代管基礎設施
- 全球可用性
- 按需付费
Purpose-Built for High-End Manufacturing專為高階製造業打造
LongDB is designed with deep domain expertise for semiconductor, display, and advanced manufacturing industries where data complexity meets mission-critical requirements.
LongDB 凭借在半導體、顯示器和先進製造業的深厚領域專業知識,專為資料複雜性與關鍵任务需求並存的業界設計。
🔬 Semiconductor Manufacturing半導體製造
The semiconductor industry generates massive volumes of data across fabrication, testing, and packaging. LongDB provides the performance and scale needed for advanced analytics and AI-driven quality control.
半導體業界在製造、測試和封装過程中產生海量資料。LongDB 提供先進分析和 AI 驅動品質控制所需的性能和規模。
Wafer Defect Classification晶圓缺陷分類
AI-powered classification of wafer defects (Center, Donut, Edge-Loc, Edge-Ring, Loc, Random) with real-time detection.
AI 驅動的晶圓缺陷分類(中心、甜甜圈、邊緣局部、邊緣環、局部、隨機),支援即時偵測。
Micro-LED Mass TransferMicro-LED 巨量轉移
Handle millions of position and optical performance data points per substrate for defect analysis and yield optimization.
處理每個基板數百萬個位置和光學性能資料點,用于缺陷分析和良率最佳化。
Panel Path Analysis面板路径分析
Track product flow through equipment with historical analysis. Identify equipment combinations that impact yield rates.
通過歷史分析追踪產品在設備間的流轉。辨識影響良率的設備組合。
History Analysis履歷分析
Calculate IV (Information Value) for equipment contribution to defect rates. Identify suspicious equipment for maintenance.
計算設備對缺陷率貢獻的 IV(信息值)。辨識需要維護的可疑設備。
🏭 Digital Manufacturing Transformation數位化製造轉型
Consolidate data from ERP, MES, PLM, and shop floor systems into a single platform. Enable real-time visibility and data-driven decision making.
將 ERP、MES、PLM 和车間系統的資料整合到單一平台。實現即時可見性和資料驅動決策。
- Unified data layer for all manufacturing systems
- Real-time production monitoring dashboards
- Predictive maintenance and quality analytics
- Supply chain optimization
- 所有製造系統的統一資料層
- 即時生產監控儀表板
- 預測性維護和品質分析
- 供應鏈最佳化
🔄 Legacy Data Warehouse Replacement傳統資料倉儲替換
Migrate from expensive legacy data warehouses to LongDB with lower TCO and better performance for modern workloads.
从昂貴的傳統資料倉儲遷移到 LongDB,以更低的 TCO 和更好的性能支援現代工作負載。
- 60%+ cost reduction vs legacy systems
- Automated schema migration tools
- SQL compatibility for smooth transition
- Parallel operation during migration
- 相比傳統系統成本降低 60% 以上
- 自動化 Schema 遷移工具
- SQL 兼容性確保平滑過渡
- 遷移期間並行執行
📡 IoT & Sensor AnalyticsIoT 與感測器分析
Process millions of sensor readings per second from manufacturing equipment, environmental monitors, and connected devices.
每秒處理來自製造設備、環境監測器和聯網設備的數百萬感測器讀數。
- Sub-second streaming ingestion
- Time-series optimized storage
- Real-time anomaly detection
- Edge-to-cloud data pipeline
- 亚秒級流式攝入
- 時序最佳化儲存
- 即時異常偵測
- 邊緣到雲資料管線
🏥 Precision Healthcare精准醫療
Integrate clinical data, genomics, imaging, and real-world evidence for precision medicine research and clinical decision support.
整合臨床資料、基因组學、影像和真實世界證據,用于精准医學研究和臨床決策支援。
- Multi-modal data integration
- HIPAA-compliant security
- ML-ready feature engineering
- Federated learning support
- 多模态資料整合
- HIPAA 合規安全
- ML 就緒特徵工程
- 聯邦學習支援
Proven Results實證效果
SEMICONDUCTOR FAB半導體晶圓厂
Faster Root Cause Analysis根因分析速度提升
Unified data access enables engineers to investigate defect patterns in minutes instead of hours, accelerating time-to-resolution.
統一資料存取使工程师能够在分钟内而非數小時内調查缺陷模式,加速問題解決。
DISPLAY MANUFACTURER顯示器製造商
Reduction in Data Pipeline Complexity資料管線複雜度降低
Eliminated ETL jobs between operational and analytical systems, reducing maintenance burden and data latency.
消除營運系統與分析系統之間的 ETL 作業,降低維護負擔和資料延遲。
PRECISION MANUFACTURING精密製造
Lower Infrastructure Costs基礎設施成本降低
Consolidated multiple data systems into a single platform, reducing licensing, hardware, and operational overhead.
將多個資料系統整合到單一平台,減少授權、硬件和運維開銷。
Platform Comparison by Category按類別平台比較
Understanding how LongDB fits in the data platform landscape. Rather than competing head-to-head with every platform, LongDB occupies a unique position as a unified Lakehouse designed for manufacturing.
了解 LongDB 在資料平台版圖中的位置。LongDB 並非與每個平台正面競爭,而是佔據獨特定位——專為製造業設計的統一湖倉一體平台。
📊 MPP Analytical DatabasesMPP 分析型資料庫
High-performance analytical query engines designed for data warehousing and business intelligence workloads.
為資料倉儲和商業智慧工作負載設計的高性能分析查詢引擎。
| Platform平台 | Strengths優勢 | Limitations局限性 | vs LongDB比較 LongDB |
|---|---|---|---|
| Teradata | Mature, proven at scale, strong in retail/finance | High cost, proprietary, limited cloud flexibility | LongDB: 60% lower TCO, open standards, hybrid cloud |
| Greenplum | Open source, PostgreSQL compatible, good ML support | Complex operations, limited streaming, aging architecture | LongDB: Modern lakehouse, better streaming, easier ops |
| Vertica | Fast analytics, good compression, mature product | Expensive licensing, proprietary format, limited AI | LongDB: Open architecture, Virtual Table extensibility, native AI integration |
| StarRocks/Doris | Fast OLAP, real-time analytics, good for dashboards | Less mature, limited ML, separate storage layer | LongDB: Unified storage+compute, stronger ML/AI |
| Teradata | 成熟,大規模驗證,零售/金融領域强势 | 成本高,專有,雲靈活性有限 | LongDB:TCO 降低 60%,開放標準,混合雲 |
| Greenplum | 開源,PostgreSQL 兼容,ML 支援良好 | 運維複雜,流處理有限,架構老化 | LongDB:現代湖倉,更好流處理,運維簡單 |
| Vertica | 分析快速,压缩好,產品成熟 | 授權昂貴,專有格式,AI 有限 | LongDB:開放架構,虛擬表可擴展性,原生 AI 整合 |
| StarRocks/Doris | OLAP 快速,即時分析,適合儀表板 | 成熟度较低,ML 有限,儲存層分離 | LongDB:統一儲存+計算,更强 ML/AI |
☁️ Cloud Data Platforms雲資料平台
Cloud-native data platforms offered by major cloud providers and independent vendors.
主要雲供應商和獨立供應商提供的雲原生資料平台。
| Platform平台 | Strengths優勢 | Limitations局限性 | vs LongDB比較 LongDB |
|---|---|---|---|
| Snowflake | Excellent UX, auto-scaling, strong ecosystem | Cloud-only, high costs at scale, limited on-prem | LongDB: Hybrid cloud, on-prem support, lower TCO |
| Databricks | Best-in-class ML, Delta Lake, strong Spark | Complex pricing, requires cloud, steep learning curve | LongDB: Simpler pricing, true hybrid, easier adoption |
| AWS Redshift | Deep AWS integration, serverless option | AWS lock-in, complex tuning, limited ML | LongDB: Multi-cloud, simpler ops, native ML |
| BigQuery | Serverless, excellent for ad-hoc, GCP integrated | GCP lock-in, unpredictable costs, no on-prem | LongDB: Predictable pricing, hybrid deployment |
| Azure Synapse | Microsoft ecosystem, Power BI integration | Azure lock-in, complex architecture, multiple engines | LongDB: Unified engine, multi-cloud, simpler |
| Snowflake | 優秀 UX,自動擴展,生態强大 | 仅限雲端,大規模成本高,無地端部署 | LongDB:混合雲,地端部署支援,更低 TCO |
| Databricks | 顶級 ML,Delta Lake,Spark 强势 | 定价複雜,需要雲,學習曲線陡峭 | LongDB:定价簡單,真正混合雲,易于採用 |
| AWS Redshift | 深度 AWS 整合,Serverless 選項 | AWS 鎖定,調優複雜,ML 有限 | LongDB:多雲,運維簡單,原生 ML |
| BigQuery | Serverless,適合即席查詢,GCP 整合 | GCP 鎖定,成本不可預測,無地端部署 | LongDB:可預測定价,混合部署 |
| Azure Synapse | 微软生態,Power BI 整合 | Azure 鎖定,架構複雜,多引擎 | LongDB:統一引擎,多雲,更簡單 |
💾 Transactional Databases (OLTP)事务型資料庫 (OLTP)
Traditional relational databases designed for transactional workloads. Note: LongDB complements these systems rather than replacing them.
為事务性工作負載設計的傳統關係型資料庫。注意:LongDB 是這些系統的補充,而非替代。
| Platform平台 | Best For最適用情境 | Analytics Limitations分析局限性 | LongDB Relationship與 LongDB 的關係 |
|---|---|---|---|
| Oracle | Enterprise OLTP, ERP backends | Expensive for analytics scale, row-based storage | CDC replication to LongDB for analytics |
| PostgreSQL | General purpose, open source | Limited horizontal scale, not for PB-scale | CDC replication to LongDB for analytics |
| MySQL | Web applications, simple OLTP | Not designed for complex analytics | CDC replication to LongDB for analytics |
| SQL Server | Microsoft stack, enterprise apps | Scaling costs high, Windows-centric | CDC replication to LongDB for analytics |
| Oracle | 企業 OLTP,ERP 后端 | 分析規模成本高,行式儲存 | CDC 複製到 LongDB 做分析 |
| PostgreSQL | 通用,開源 | 水平擴展有限,不適合 PB 級 | CDC 複製到 LongDB 做分析 |
| MySQL | Web 應用,簡單 OLTP | 非為複雜分析設計 | CDC 複製到 LongDB 做分析 |
| SQL Server | 微软技术栈,企業應用 | 擴展成本高,以 Windows 為中心 | CDC 複製到 LongDB 做分析 |
🔗 Distributed NoSQL & NewSQL分布式 NoSQL 與 NewSQL
Distributed databases designed for high-scale transactional or specialized workloads.
為大規模事务或專業工作負載設計的分布式資料庫。
| Platform平台 | Best For最適用情境 | Analytics Limitations分析局限性 | vs LongDB比較 LongDB |
|---|---|---|---|
| CockroachDB | Distributed ACID, global transactions | Not optimized for analytical queries | Different use case; LongDB for analytics layer |
| TiDB | HTAP (hybrid transactional/analytical) | Trade-offs in both OLTP and OLAP performance | LongDB: Focused analytics excellence |
| Cassandra | High write throughput, time-series | Limited SQL, no complex joins | Can feed data to LongDB for analytics |
| MongoDB | Document storage, flexible schema | Not designed for complex analytics | Semi-structured data → LongDB for analytics |
| CockroachDB | 分布式 ACID,全球事务 | 未针對分析查詢最佳化 | 不同用例;LongDB 用于分析層 |
| TiDB | HTAP(混合事务/分析) | OLTP 和 OLAP 性能都有折衷 | LongDB:專注分析卓越性 |
| Cassandra | 高寫入吞吐量,時序 | SQL 有限,無複雜連結 | 可將資料輸入 LongDB 做分析 |
| MongoDB | 文件儲存,靈活 Schema | 非為複雜分析設計 | 半結構化資料 → LongDB 做分析 |
Why Choose LongDB為什麼選擇 LongDB
🎯 End-to-End Platform端到端平台
Unlike competitors that require cobbling together multiple products, LongDB provides a complete, integrated solution from ingestion to insight.
不同于需要拼凑多個產品的競爭對手,LongDB 提供从資料攝取到洞察的完整整合解決方案。
- No need for separate ETL tools
- Built-in BI and visualization
- Integrated Data Science Studio & ML
- Single vendor, single contract
- 無需單獨的 ETL 工具
- 內建 BI 和視覺化
- 整合資料科學工作室與 ML
- 單一供應商,單一合同
☁️ True Hybrid Cloud真正的混合雲
Deploy anywhere—on-premises, private cloud, or public cloud—with the same platform, APIs, and user experience.
任意部署——地端、私有雲或公有雲——相同的平台、API 和用户體驗。
- Air-gap deployment for security
- Data sovereignty compliance
- Burst to cloud for peak loads
- Consistent ops across environments
- 物理隔離部署保障安全
- 資料主权合規
- 峰值負載彈性擴展到雲
- 跨環境一致運維
🏭 Manufacturing DNA製造業基因
Built by a team with deep expertise in semiconductor and high-tech manufacturing. Pre-built solutions for common industry challenges.
由在半導體和高科技製造業擁有深厚專業知識的團隊打造。针對常見業界挑戰的預置解決方案。
- Semiconductor analytics templates
- MES/ERP connectors (SAP, Oracle)
- Quality and yield models
- Industry-specific training & support
- 半導體分析模板
- MES/ERP 連結器(SAP、Oracle)
- 品質和良率模型
- 業界特定培训與支援
💰 Superior TCO卓越的 TCO
Achieve 60%+ cost savings compared to legacy data warehouses and competitive cloud platforms.
相比傳統資料倉儲和競爭雲平台,實現 60% 以上的成本節省。
- Competitive licensing
- Efficient resource utilization
- Reduced integration costs
- Lower operational overhead
- 有競爭力的授權定价
- 高效資源利用
- 降低整合成本
- 更低運維開銷
Becoming the Global Leader in Manufacturing Data Intelligence成為全球製造業資料智慧領導者
LongDB Technology envisions a future where every manufacturing enterprise can harness the full potential of their data through intelligent, unified, and accessible platforms. We're building the foundation for the AI-powered factory of the future.
龍迪數智科技致力於建構一個未來,讓每家製造企業都能通過智慧、統一、易用的平台充分釋放資料潛力。我們正在為 AI 驅動的未來工廠奠定基礎。
Our Vision & Mission我們的願景與使命
🎯 Vision願景
To become the world's leading data intelligence platform for manufacturing, empowering enterprises across Asia and globally to transform data into competitive advantage through unified lakehouse architecture and AI-native capabilities.
成為全球領先的製造業資料智慧平台,通過統一湖倉架構和 AI 原生能力,賦能亞洲及全球企業將資料轉化為競爭優勢。
🚀 Mission使命
To deliver an end-to-end data platform that eliminates complexity, reduces costs, and accelerates time-to-insight for manufacturing and high-tech enterprises—making enterprise-grade data intelligence accessible to all.
提供端到端資料平台,消除複雜性、降低成本、加速製造業和高科技企業的洞察時間——让企業級資料智慧觸手可及。
What's Coming Next即將推出
SupraBrain 2.0SupraBrain 2.0
Enhanced agentic capabilities with multi-agent orchestration, agent workspace for collaborative workflows, multi-step reasoning, and improved NL-to-SQL accuracy. Integration with GPT, Claude, Gemini, Qwen, and DeepSeek.
增强的智慧代理能力,支援多智慧代理協同、智慧代理工作空間、多步推理和改進的自然語言轉 SQL 準確性。與 GPT、Claude、Gemini、Qwen 和 DeepSeek 整合。
Fusion Vector Search & Enhanced RAG融合向量搜尋與增强 RAG
Fusion vector database integration combining dense and sparse retrieval for superior semantic search. Enhanced RAG with hybrid search, re-ranking, and multi-modal document understanding for enterprise AI applications.
融合向量資料庫整合,結合稠密和稀疏檢索實現卓越的語意搜尋。增强的 RAG 支援混合搜尋、重排序和多模态文件理解,賦能企業級 AI 應用。
Multi-Cloud Federation多雲聯邦
Query data across multiple cloud providers and on-premises deployments with a single SQL interface. True hybrid cloud with unified governance.
通過單一 SQL 接口查詢多個雲供應商和地端部署的資料。真正的混合雲統一治理。
Industry Solutions業界解決方案
Pre-packaged solutions for semiconductor, automotive, and high-end manufacturing with domain-specific data models, dashboards, and ML models.
為半導體、汽車和高階製造業預置的解決方案,包含領域特定資料模型、儀表板和 ML 模型。
Go-to-Market Approach市场推广策略
🌏 Asia-First Strategy亞洲優先策略
Deep focus on Greater China, Taiwan, Korea, and Southeast Asia where manufacturing drives economic growth. Local teams, local language support, and partnerships with regional system integrators.
深耕大中华區、台湾、韩国和东南亚等製造業驅動經濟增長的地區。地端團隊、地端語言支援以及與區域系統整合商的合作。
🏭 Vertical Focus垂直領域專注
Concentrated expertise in semiconductor, display, and high-tech manufacturing. Build reference architectures and proof points that resonate with industry-specific challenges.
專注于半導體、顯示器和高科技製造業。建構與業界特定挑戰產生共鳴的参考架構和驗證案例。
🤝 Partner Ecosystem合作伙伴生態
Strategic partnerships with cloud providers (AWS, Azure, GCP, Alibaba, Tencent, Huawei), system integrators, and technology vendors to extend reach and deliver comprehensive solutions.
與雲端供應商(AWS、Azure、GCP、阿里巴巴、騰訊、華為)、系統整合商和技術供應商的策略合作,擴大覆蓋範圍並提供全面解決方案。
LongDB Technology龍迪數智科技
LongDB Technology (龍迪數智科技) is a Beijing-based data platform company founded by industry veterans with deep experience in enterprise data management, AI/ML, and semiconductor manufacturing.
Our team combines expertise from leading global technology companies with intimate knowledge of Asian market requirements, regulatory environments, and business practices.
We believe that the future of enterprise data is unified, intelligent, and accessible. LongDB is building that future—one customer at a time.
龍迪數智科技(LongDB Technology)是一家資料+AI平台公司,由在企業資料管理、AI/ML 和半導體製造領域擁有豐富經驗的業界資深人士創立。
我們的團隊融合了來自全球領先科技公司的專業知識,同時深谙亞洲市场需求、法規環境和商業惯例。
我們堅信企業資料的未來是統一的、智慧的、易于存取的。LongDB 正在建構這個未來——每次服務一位客戶。