BTrDB vs CnosDB
BTrDB
btrdb.readthedocs.io
CnosDB
cnosdb.comSide by side
| Figure | BTrDB | CnosDB |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | — | — |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 2 |
| Spec score · Time-Series Databases | 8.8 (#3) | 8.5 (#6) |
| Installation | The maker recommends installing btrdb-python with pip and offers data-science and all-optional-dependency extras. | The installation guide shows Docker installation and directs Ubuntu and Debian users to install through apt; it says to contact CnosDB for the Enterprise package. |
| Integrations | The Python documentation includes examples using Dash and Plotly to plot data queried from BTrDB. | The ecosystem integration page lists LangChain, Grafana, Jaeger, Kafka, Prometheus, Telegraf, TensorFlow, and Vector. |
| License | The BTrDB server repository identifies its license as MIT. | The official site says the standalone, distributed, and ecosystem tools use the AGPL-3.0 open-source license. |
| Product | BTrDB is a time-partitioned, version-annotated clustered time-series database for high-density univariate data. | CnosDB is an open-source distributed time-series database designed for high performance, compression, and ease of use. |
| Security | The documentation describes TLS access on port 4411 and API-key authentication, which requires the TLS port. | The configuration documentation provides optional TLS certificate and private key settings. |
Plans
In their own words
BTrDB
BTrDB is a free, MIT-licensed, self-hosted time-series database for dense, high-precision univariate data. It partitions data by time, supports clustered deployments, and records stream changes as new versions that queries can target. Streams have unique UUIDs and can be grouped into collections with tags and annotations. The Python btrdb package supports nanosecond-timestamp queries and insertion through Stream.insert, PyArrow tables, or pandas DataFrames. Statistical queries can return minimum, maximum, mean, count, and standard deviation without reading every underlying point. StreamSets can be filtered and converted to pandas DataFrames or CSV files. Documentation shows Dash and Plotly visualization, Ray-worker serialization, TLS on port 4411, and API-key authentication requiring that TLS port. Arrow-based tabular methods are documented for commercial customers with Arrow-enabled servers. BTrDB reports measured cluster throughput and compression figures, and describes smart-grid aggregation at city or country scale as one target use case.
CnosDB
CnosDB is an open-source distributed time-series database for workloads such as IoT, industrial internet, connected vehicles, and IT operations. It supports standard SQL, time-based aggregation, and a DataFrame API. Data can be written without a predefined schema, including out of order, and historical data can be replenished. Ingestion methods include SQL, Line Protocol, OpenTSDB, Elasticsearch bulk, Loki, NDJSON, and OpenTelemetry. Deployment options include standalone, distributed, and storage-compute separated modes, on public, private, or hybrid clouds. The documentation describes horizontal scaling for storage and stateless compute nodes. Integrations include Grafana, Prometheus, Telegraf, JDBC, and a Python SDK; the open-source Python connector provides a PEP 249 interface for SQLAlchemy and pandas. Import and export formats include PARQUET, CSV, and JSON with AWS S3, Google Cloud Storage, and Azure Blob Storage. CnosDB documents retention policies, multi-tenancy, and role-based permissions, as well as optional TLS certificate and private-key settings. Community Edition is free under AGPL-3.0.