Cloud Native Time-Series Database
CnosDB 2.0

2.0 Design Ideas

CnosDB is a high-performance, high-compression, and easy-to-use open-source distributed time-series database. It is primarily used in fields such as IoT, industrial internet, connected cars, and IT operations. All of the code is open-sourced and available on GitHub.

In its design, we fully utilize the characteristics of time-series data, including structured data, non-transactions, fewer deletions and updates, more writes and less reads, etc. As a result, CnosDB has a number of advantages that set it apart from other time-series databases:

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Community Edition

Free, open source, eco-friendly

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Enterprise Edition

Private cloud, expert support

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CnosDB Cloud

Serverless, Out-of-the-box

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CnosDB Embedded

A collaborative embedded time-series database for cloud and edge

Product advantages

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High Performance

CnosDB addresses the issue of time-series data expansion and theoretically supports unlimited time-series data. It supports aggregate queries along the timeline, including queries divided by equal intervals, queries divided by enumeration values of a column, and queries divided by the length of the time interval between adjacent time-series records. It also has caching capabilities for the latest data and the cache space can be configured for fast access to the latest data.

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Easy to use

CnosDB provides clear and simple interfaces, easy configuration options, standard SQL support, seamless integration with third-party tools, and convenient data access functions. It supports schema-less writing mode and supports historical data supplement(including out of order writing).

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Cloud Native

CnosDB has a native distributed design, data sharding and partitioning, separation of storage and computing, Quorum mechanism, Kubernetes deployment and complete observability, ensuring final consistency. It can be deployed in public clouds, private clouds, and hybrid clouds. t also supports multi-tenancy and has role-based permission control. The computing and storage nodes support horizontal scaling.

Architecture