BTrDB vs Warp 10
BTrDB
btrdb.readthedocs.io
Warp 10
warp10.ioSide by side
| Figure | BTrDB | Warp 10 |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| 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) | 8.1 (#16) |
| Installation | The maker recommends installing btrdb-python with pip and offers data-science and all-optional-dependency extras. | The download page describes binary installation on your own infrastructure and a Docker image that includes Warp 10, WarpStudio, and Sensision. |
| Integrations | The Python documentation includes examples using Dash and Plotly to plot data queried from BTrDB. | The platform can fetch data from SQL and NoSQL databases, document stores, other time series databases, and monitoring platforms. |
| Product | BTrDB is a time-partitioned, version-annotated clustered time-series database for high-density univariate data. | Warp 10 describes itself as a time series platform for storing and analyzing time series and Geo Time Series data. |
| Security | The documentation describes TLS access on port 4411 and API-key authentication, which requires the TLS port. | Warp 10 uses cryptographic tokens to control access, and its ingress API requires a valid write token in the X-Warp10-Token header. |
| Support | The documentation invites users to submit pull requests or open a GitHub issue for additions or corrections. | Warp 10 documentation directs users to its community Slack to report issues or missing documentation. |
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.
Warp 10
Warp 10 is a free, open-source platform for collecting, storing, and analyzing time series and Geo Time Series data, including sensor data. It runs as a server that accepts HTTP requests for ingestion and WarpScript execution, and supports API, Linux, macOS, web, Windows, and self-hosted deployments. The platform is available in Standalone, Standalone+, and Distributed versions whose main difference is storage-engine implementation. Standalone uses LevelDB and is described as suitable for a few tens of millions of time series and a few hundreds of billions of datapoints; larger needs are directed to Distributed, which uses FoundationDB. Warp 10 includes more than 1,300 time-series functions. Installation can use binaries on your infrastructure or a Docker image containing Warp 10, WarpStudio, and Sensision. Integrations include Jupyter, Zeppelin, Spark, Flink, MQTT, BACNet, NodeRed, NiFi, SQL and NoSQL sources, Grafana, and PowerBI. Ingestion supports HTTP POST, WebSocket, UDP, MQTT, and Kafka. Cryptographic READ and WRITE tokens control access, and metadata encryption is enabled by default.