BTrDB
BTrDB is an open-source, self-hosted time-series database designed for high-density univariate data, including dense streaming telemetry and high-precision s…
What BTrDB is
BTrDB is an open-source, self-hosted time-series database designed for high-density univariate data, including dense streaming telemetry and high-precision sensor data. It partitions data by time, supports clustered deployments and records changes to a stream as new versions, so queries can target a particular version. Streams have unique UUIDs and can be grouped into collections with tags and annotations. The documented Python client connects to a BTrDB server and supports stream lookup and retrieval, including queries using nanosecond timestamps. Statistical queries can return minimum, maximum, mean, count and standard deviation without reading every underlying point; query time is proportional to the number of results. Data can be inserted through the Python Stream.insert API, PyArrow tables or pandas DataFrames. StreamSets can be filtered and converted to pandas DataFrames or CSV, and documentation includes Dash, Plotly and Ray examples. Arrow-based tabular methods are documented for commercial customers with Arrow-enabled servers. The documentation covers TLS access on port 4411 and API-key authentication, which requires that TLS port. Data requests are fully materialized; generator-based processing is described as planned for a future release. The server repository identifies its license as MIT.
Good
- Open-source server repository identifies an MIT license
- Queries can use nanosecond timestamps
- Stream changes are retained as versions
- Supports Python, PyArrow and pandas insertion
- Statistical queries return five summary measures
Watch out
- Arrow tabular methods require commercial customers and enabled servers
- Data requests are fully materialized
- Self-hosted deployment requires operating the software
Who it suits
BTrDB suits teams that need to deploy a database for dense telemetry or high-precision sensor data and work with it through Python. Its self-hosted model also fits users prepared to operate a clustered deployment.
Verdict
BTrDB combines versioned time-series storage with Python access and several data conversion paths. Consider the materialized-request behavior and commercial restriction on Arrow-based tabular methods when planning how to use it.
Plans and prices
From BTrDB's own pricing page, checked 11 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| BTrDB | Free | No plan or usage limits stated on the opened pages |
The facts
Each one read from BTrDB's own pages, with the date it was checked.
What it does
- Aggregates
- StatPoint queries can return min, max, mean, count, and standard deviation, with query time proportional to the number of results.checked 4 Oct 2026
- Client library
- The documentation provides Python access to BTrDB through the btrdb package.checked 4 Oct 2026
- Commercial feature limit
- The documentation says native tabular data formats are enabled for commercial customers.checked 11 Oct 2026
- Compression
- The documentation reports 2.93x compression for high-precision nanosecond streams.checked 11 Oct 2026
- Data formats
- StreamSets can be filtered and converted to formats including pandas DataFrames and CSV files.checked 4 Oct 2026
- Data integrations
- The documentation describes StreamSet conversions to pandas DataFrames and CSV, and Arrow-enabled methods for tabular data.checked 11 Oct 2026
- Data request behavior
- The docs state that data requests are fully materialized and that generator-based processing is planned for a future release.checked 11 Oct 2026
- Install
- The maker recommends installing btrdb-python with pip and also documents installation with Anaconda.checked 4 Oct 2026
- Installation
- The maker recommends installing btrdb-python with pip and offers data-science and all-optional-dependency extras.checked 11 Oct 2026
- Integrations
- The Python documentation includes examples using Dash and Plotly to plot data queried from BTrDB.checked 4 Oct 2026
- License
- The BTrDB server repository identifies its license as MIT.checked 11 Oct 2026
- Nanosecond timestamps
- BTrDB’s example client uses nanosecond timestamps to query time-series values.checked 4 Oct 2026
- Parallel processing
- The client documents a serializer for passing BTrDB connections, streams, and StreamSets to Ray workers.checked 4 Oct 2026
- Performance
- The documentation reports 53 million inserted values per second and 119 million queried values per second on a measured four-node cluster of large EC2 nodes.checked 11 Oct 2026
- Product
- BTrDB is a time-partitioned, version-annotated clustered time-series database for high-density univariate data.checked 11 Oct 2026
- Python client
- The documented btrdb-python library connects to a BTrDB server and supports stream lookup and time-series retrieval.checked 11 Oct 2026
- Query summaries
- Statistical points can provide min, max, mean, count, and standard deviation without reading every underlying point.checked 11 Oct 2026
- Security
- The documentation describes TLS access on port 4411 and API-key authentication, which requires the TLS port.checked 4 Oct 2026
- Self-hosting and audience
- The project describes BTrDB as deployable software and says Smartgrid.store targets very large city- or country-scale aggregation from smart-grid devices, while noting BTrDB can support other use cases.checked 4 Oct 2026
- Stream collections
- Streams have unique UUIDs and can be grouped into collections with tags and annotations for metadata.checked 4 Oct 2026
- Support
- The documentation invites users to submit pull requests or open a GitHub issue for additions or corrections.checked 11 Oct 2026
- Use case
- The documentation describes BTrDB as designed for dense, streaming telemetry, including high-precision sensor data.checked 11 Oct 2026
- Versioning
- Data is version annotated, allowing queries against a specific stream version for reproducible results.checked 11 Oct 2026
- Visualization
- The docs show examples using BTrDB data with Dash and Plotly.checked 11 Oct 2026
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