BTrDB vs TimechoDB
BTrDB
btrdb.readthedocs.io
TimechoDB
timecho-global.comSide by side
| Figure | BTrDB | TimechoDB |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | Yes |
| Open source | — | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Time-Series Databases | 8.8 (#3) | 7.5 (#29) |
| Integrations | The Python documentation includes examples using Dash and Plotly to plot data queried from BTrDB. | The ecosystem guide lists integrations including Kafka, Flink, Spark, Grafana, DataEase, DBeaver, ThingsBoard, Ignition, and Telegraf. |
| Product | BTrDB is a time-partitioned, version-annotated clustered time-series database for high-density univariate data. | TimechoDB is an enterprise-grade product based on Apache IoTDB with enhanced performance, expanded features, and customization. |
| Security | The documentation describes TLS access on port 4411 and API-key authentication, which requires the TLS port. | The product page lists audit logs and system whitelisting, while the current user guide documents account, permission, connection, communication, storage, and audit security features. |
| Support | The documentation invites users to submit pull requests or open a GitHub issue for additions or corrections. | The product page describes professional support with service-level agreements and lists expert support and usage training in its feature comparison. |
| Use case | The documentation describes BTrDB as designed for dense, streaming telemetry, including high-precision sensor data. | Timecho describes the product as designed for IoT and industrial time-series data management. |
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.
TimechoDB
TimechoDB has no write-up on Specifiction yet; its figures are above.