Axibase Time Series Database vs BTrDB
Axibase Time Series Database
axibase.comBTrDB
btrdb.readthedocs.ioSide by side
| Figure | Axibase Time Series Database | BTrDB |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 1 |
| Spec score · Time-Series Databases | 7.6 (#25) | 8.8 (#3) |
| Integrations | Axibase Collector supports data collection jobs for AWS, Docker, HTTP, JDBC, JMX, Kafka, SNMP, and other sources. | The Python documentation includes examples using Dash and Plotly to plot data queried from BTrDB. |
| Security | ATSD supports form, basic, and token authentication; tokens can expire automatically and be restricted by IP address. | The documentation describes TLS access on port 4411 and API-key authentication, which requires the TLS port. |
| Support | The documentation lists commercial support through its Support Desk and trial-period support by email. | The documentation invites users to submit pull requests or open a GitHub issue for additions or corrections. |
| Visualization | Users can create portals with custom layouts and any number of widgets to visualize series. | The docs show examples using BTrDB data with Dash and Plotly. |
Plans
In their own words
Axibase Time Series Database
Axibase Time Series Database has no write-up on Specifiction yet; its figures are above.
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.