Welcome to the KxSystems GitHub, the home of official open-source repositories from KxSystems.

Foundational projects for kdb+/q.

• kdb - Companion files for kdb+ and q
• kdb-taq - Tools and schemas for TAQ-style data in kdb+
• kdb-tick - Tickerplant, RDB and pub/sub scripts

Language bindings for interacting with kdb+.

• pykx - Python‑first interface to kdb+/q
• embedR - Embed R inside q
• javakdb - kdb+ IPC interface for Java
• jdbc - JDBC client for kdb+
• csharpkdb - .NET client library for interfacing with kdb+
• ffi - Foreign Function Interface for kdb+
• rkdb - R client library for kdb+
• jupyterq - Jupyter kernel for kdb+
• kxkdb - kdb+ interface for Rust

KDB‑X introduced a module framework to q. Projects in this section are incompatible with earlier versions of kdb+.

• logging - Logging utilities for KDB-X
• printf - Formatted printing mirroring printf C99 standard
• fusionx - Portable native library wrappers for KDB-X
• datagen - Functions for generating synthetic data for various domains
• taq - Parse NYSE TAQ psv files and persist results in kdb+ format.
• dbmaint - Functions for making changes to a persisted kdb+ database.
• ax - Components from the ax-libraries .

Connectivity with external formats and messaging platforms.

KDB-X has a native parquet integration that is recommended over the parquet read capabilities provided via arrowkdb. link

• arrowkdb - Apache Arrow & Parquet integration
• hdf5 - HDF5 file support for kdb+
• protobufkdb - kdb+ integration with Google Protocol Buffers
• ldap - kdb+ integration with LDAP
• mqtt - MQTT messaging protocol interface
• solace - Solace middleware client for kdb+
• kafka - kdb+ to Apache Kafka adapter

Machine Learning and Natural Language Processing related repositories.

KDB-X has an ai module that provides vector database capabilities to kdb+ data stores that is useful for Retrieval Augmented Generation. link

• ml - Machine Learning Toolkit
• nlp - Natural Language Processing library
• automl - Automated Machine Learning Framework for kdb+

Learning resources, example projects, and official documentation.

• docs - Source repository for KX documentation
• cookbook - Companion files to the kdb+ Knowledge Base
• tutorials - Step‑by‑step tutorials and walkthroughs
• mlnotebooks - Demonstration notebooks for Machine Learning
• accelerators-samples - Demonstration of Accelerator APIs accessed via REST

Developer tools, performance benchmarks, and productivity extensions.

• kx-vscode - Visual Studio Code extension for kdb+/q
• kx-vscode-auth - Authentication support for the VS Code extension
• tsbs - Time Series Benchmark Suite
• nano - Raw I/O benchmarking utilities
• compression-test-taq - Compression performance testing for TAQ data