Amazon Timestream
Serverless time-series database for IoT, metrics, and operational telemetry
CnosDB
High-performance distributed time-series database for IoT and observability
CnosDB is a Rust-based distributed time-series database optimized for IoT, industrial internet, and IT operations with high compression, standard SQL support, and cloud-native architecture.
Overview
Purpose-Built for Time-Series Workloads
CnosDB is a distributed time-series database designed for high-cardinality data in IoT, industrial internet, connected vehicles, and IT operations. Written in Rust, it leverages the inherent characteristics of time-series data—structured, write-heavy, minimal updates—to deliver exceptional performance and compression.
Cloud-Native Architecture
The platform features native distributed design with separation of storage and compute, data sharding, and horizontal scalability. Deploy on public, private, or hybrid clouds with Kubernetes support. Multi-tenancy and role-based access control enable secure, isolated workloads. The Quorum mechanism ensures eventual consistency across nodes.
Developer Experience
CnosDB supports standard SQL queries, schema-less writes, and out-of-order data ingestion for historical backfill. Aggregate queries along timelines include equal-interval grouping and enumeration-based partitioning. Integration with Telegraf, InfluxDB line protocol, and Prometheus remote read provides compatibility with existing observability stacks. A configurable cache layer accelerates access to recent data, while bulk loading handles high-volume imports efficiently.
Highlights
Unlimited time-series scalability with advanced timeline aggregation and configurable caching
Standard SQL interface with schema-less writes and out-of-order data support
Cloud-native distributed architecture with storage-compute separation and horizontal scaling
Native integration with InfluxDB line protocol, Telegraf, and Prometheus remote read
Pros
- High compression and performance optimized for time-series characteristics
- Flexible deployment across public, private, and hybrid cloud environments
- Standard SQL reduces learning curve and enables broad tooling compatibility
- Multi-tenancy and RBAC support enterprise isolation and security requirements
Considerations
- Requires Rust toolchain, CMake, FlatBuffers, and Protobuf for source builds
- Relatively newer project compared to established time-series databases
- Documentation and community resources may be less extensive than mature alternatives
- Cluster deployment complexity requires careful configuration and operational expertise
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Fit guide
Great for
- IoT platforms ingesting high-cardinality sensor data from distributed devices
- Industrial monitoring systems requiring long-term retention and fast aggregations
- Connected vehicle telemetry with irregular data arrival patterns
- IT operations teams needing SQL-compatible observability storage with cloud portability
Not ideal when
- Transactional workloads requiring ACID guarantees and frequent updates
- Small-scale projects where operational overhead outweighs distributed benefits
- Teams without Rust or distributed systems expertise for custom deployments
- Use cases demanding mature ecosystem integrations and extensive third-party tooling
How teams use it
IoT Sensor Network Monitoring
Ingest millions of sensor readings per second with automatic compression, query historical trends via SQL, and cache recent values for real-time dashboards.
Industrial Equipment Predictive Maintenance
Store years of machine telemetry, perform timeline-based aggregations to detect anomalies, and backfill historical data without disrupting live ingestion.
Connected Vehicle Fleet Analytics
Handle irregular GPS and diagnostic data from thousands of vehicles, scale storage and compute independently, and integrate with existing Telegraf pipelines.
Multi-Tenant SaaS Observability Platform
Isolate customer metrics with RBAC, deploy across hybrid cloud regions, and expose Prometheus-compatible endpoints for seamless Grafana integration.
Tech snapshot
Rust99%
Shell1%
Lua1%
Makefile1%
Dockerfile1%
RenderScript1%
Frequently asked questions
What platforms does CnosDB support?
CnosDB runs on Linux x86 (x86_64-unknown-linux-gnu) and Darwin ARM (aarch64-apple-darwin). Docker images are available for simplified deployment.
Does CnosDB support SQL queries?
Yes, CnosDB provides standard SQL support for queries, including aggregate functions and timeline-based grouping. It also supports InfluxDB line protocol for writes and Prometheus remote read for queries.
Can CnosDB handle out-of-order data?
Yes, CnosDB supports schema-less writing and out-of-order data ingestion, enabling historical data backfill without impacting current operations.
How does CnosDB scale?
CnosDB features a distributed architecture with separation of storage and compute, data sharding, and horizontal scaling of both compute and storage nodes. It supports Kubernetes deployment for cloud-native orchestration.
What ingestion methods are supported?
CnosDB accepts data via SQL INSERT statements, InfluxDB line protocol, bulk loading, and Telegraf integration. This flexibility supports diverse data sources and migration scenarios.
Project at a glance
Stable- Stars
- 1,738
- Watchers
- 1,738
- Forks
- 317
LicenseAGPL-3.0
Repo age4 years old
Last commit4 months ago
Primary languageRust
Last synced 3 hours ago