To design and develop a high performance, high compression ratio, highly available, distributed cloud native time series database, which meets the following objectives.
Time Series Database
- Extensibility, theoretically support time series without upper limit, completely solve the problem of time series inflation, support horizontal/vertical expansion.
- Separate storage and computation. Compute nodes and storage nodes can expand and shrink independently.
- High-performance storage and low cost, high-performance I/O stacks, cloud disk and object storage for storage tiering
- Query engine supports vectorized queries.
- Supports multiple timing protocols to write and query, and provides external components to import data.
Cloud Native
- Supports cloud native, making full use of the convenience brought by cloud infrastructure and integrating into cloud native ecology.
- High availability, second-level fault recovery, multi-cloud, and multi-zone disaster recovery and preparedness.
- Native support multi-tenant, pay-as-you-go.
- CDC, logs can be subscribed to and distributed to other nodes.
- More configurable items are provided to meet the complex requirements of public cloud users in multiple scenarios.
- Cloud edge - end collaboration provides the edge - end integration capability with the public cloud
- Converged OLAP/CloudAI data Ecosystem on the cloud.
| 产品特性 | 时间节点 |
|---|---|
| 2.0 Stand-alone Beta | 2022.10 |
| 2.0 Distribution Beta | 2022.12 |
| Cloud Trial on AWS | 2023.Q1 |
| Enterprise Service | 2023.Q2 |