BTrDB vs kdb+
BTrDB
btrdb.readthedocs.io
kdb+
kx.comSide by side
| Figure | BTrDB | kdb+ |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 2 |
| Spec score · Time-Series Databases | 8.8 (#3) | 7.9 (#19) |
| 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. | KX says kdb+ ingests and analyzes real-time data in memory and delivers sub-millisecond performance for time-critical workloads. |
| Security | The documentation describes TLS access on port 4411 and API-key authentication, which requires the TLS port. | kdb+ can use SSL/TLS to encrypt connections with OpenSSL, configured with certificates and keys. |
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.
kdb+
kdb+ is a time-series database and analytics engine from KX, built around the q vector language. It captures and analyzes real-time and historical data for time-sensitive workloads. KX describes in-memory ingestion and analysis with sub-millisecond performance. Its storage layout separates newest in-memory records in an RDB, recent disk data in an IDB, and long-term columnar archives in an HDB. Query options include q and q-SQL, with support for Python, Java, C#, C++, Rust, R, and open-source libraries. Data can arrive through tickerplants, feed handlers, batch mode, TCP/IP, Apache Kafka, or supported programming languages. KX describes applications in trading, fraud detection, and IoT monitoring across Capital Markets, Defense, and High-Tech Manufacturing. Deployments cover Linux, macOS, Windows, APIs, and self-hosted environments, with cloud documentation for AWS, Google Cloud Platform, and Microsoft Azure. SSL/TLS connections use OpenSSL certificates and keys.