AI-Native Multimodal
Data Intelligence Platform
Flexible Deployment, Expert Support, Mutual Growth
A hyper-converged, cloud-native database that unifies structured and unstructured data across OLTP, OLAP, and vector workloads. Its containerized architecture delivers a revolutionary Git for Data experience for massive datasets.

One engine for all your data. Store, analyze, and vectorize structured data, JSON, text, and media in a single platform. With built-in vector search and full-text indexing, we provide the real-time foundation for RAG and AI applications without complex stacks.
Elastic scalability with zero burden. Experience true Serverless architecture that scales to zero when idle. Fully compatible with the MySQL 8.0 ecosystem, allowing you to migrate seamlessly while paying only for actual compute usage.
Accelerate AI development cycles. Leverage zero-copy data branching to create instant sandboxes for Agent testing. Share real-time data securely across teams and use Time Travel to restore data to any historical point instantly.
Rock-solid stability for mission-critical apps. Built for resilience with robust Disaster Recovery (CDC) and snapshot capabilities. Ensure business continuity and data security while handling massive concurrent analytical workloads.
DataX, Canal, Kettle, SeaTunnel, Flink CDC
Spark, Flink
Superset, Tableau, FineBI, Yonghong BI
DolphinScheduler
Dify, LangChain, MCP Protocol

Seamlessly handles mixed OLTP and OLAP traffic with storage-compute separation and strict workload isolation, ensuring zero interference between real-time transactions and complex batch analytics.

Accelerates innovation with zero-copy data branching. Instantly create, manage, and switch data environments for development, testing, and AI training with unprecedented agility.

Unifies the storage and querying of structured data alongside unstructured assets — text, images, audio, and video—within a single, integrated platform.

Combines native vector indexing with full-text search to deliver high-precision hybrid retrieval, powering the next generation of GenAI applications.

Deploys ML models via UDFs and connects directly to LLMs through function calls, ensuring full compatibility with your existing AI infrastructure.

Ensures business continuity through multi-layered backup strategies (logical, physical, snapshot) and a transaction-log-based active-active architecture.