AI-Native Database Service is an all-in-one intelligent data development platform that provides capabilities such as data analytics, database O&M, data asset management, AI agent development, and data preparation. Choose a scenario below to get started with the feature that best meets your needs.
Prerequisites
An Alibaba Cloud account is created, and identity verification is complete.
If you use a RAM user, make sure the RAM user is granted the required permissions for the target feature.
Access the AI-Native Database Service console
Log on to the AI-Native Database Service console.
The console homepage defaults to the Super Agent page and displays entry cards for each feature. You can click a card to go to the corresponding feature, or use the left-side navigation pane to switch between features.
Area | Feature | Status | Description |
-- | GA | The unified conversational entry point on the homepage. Describe your task, and Super Agent recommends the appropriate solution and feature.. | |
GA | Offers ready-to-use data skills and knowledge bases to help you extend agent capabilities. | ||
Agent Data Gateway | Coming soon | A unified, secure access layer between AI agents and enterprise data sources. Provides identity management, access control, and audit trails. | |
Data Agent | GA | Performs natural language-driven data analysis and automatically generates insight reports. | |
Public preview (Beta) | An AI prediction engine powered by swarm intelligence that supports trend and demand forecasting. Free during public preview. | ||
GA | Provides intelligent database diagnostics and O&M, covering performance analysis, slow SQL optimization, and schema governance. | ||
Invite preview | An intelligent data collection agent for multimodal data that supports web scraping, file parsing, and data transfer. | ||
Agent Developer Platform - Custom Development | GA | Deploy an enterprise-grade Dify platform with one click and build AI agent applications through low-code visual orchestration. | |
GA | A RAG engine based on deep document understanding for building high-quality knowledge Q&A applications. | ||
GA | An integrated data O&M and development platform that supports data pipeline orchestration and automation. | ||
GA | An open source backend-as-a-service platform that provides database, authentication, storage, and real-time subscription capabilities. | ||
AI Data Assets | GA | Automatically inventories data assets, generates metadata knowledge, and supports natural language asset queries. | |
GA | A SQL console integrated with Data Copilot for natural language database queries and management. | ||
AI Data Preparation | GA | Performs intelligent parsing of multimodal data and builds knowledge bases, serving as the data foundation for RAG applications. |
Scenarios
AI-Native Database Service provides a rich set of features for data analytics, database O&M, AI agent development, and more. The following table lists common scenarios to help you get started:
Scenario | Target audience | Description |
Data analysts, business users | Describe your analytics requirements in natural language, and Analytics Agent automatically performs data comprehension, analysis, and report generation. You can obtain data-driven business insights without writing SQL. | |
DBAs, O&M engineers | Use DAS Agent to perform intelligent diagnostics on database instances, covering scenarios such as performance analysis, slow SQL optimization, and schema governance. DAS Agent supports unified O&M across multiple database engines. | |
AI developers, application developers | Deploy an enterprise-grade Dify platform with one click and build AI agent applications through low-code visual orchestration. Supports three logon methods: DMS account, Dify account, and IDaaS. The platform provides built-in model integration, knowledge base management, and a plugin ecosystem. | |
Data administrators, database developers | Use Meta Agent to automatically inventory data assets, generate metadata knowledge such as business descriptions and data lineage for tables and columns, and perform interactive data queries and asset management through natural language. | |
Knowledge base builders, data engineers | Create a RAGFlow knowledge base instance, connect to data sources such as OSS or DingTalk, and build an enterprise knowledge base. Supports enhanced parsing and semantic retrieval across multiple document formats, serving as the data foundation for RAG applications. |