KDB-X Roadmap

This page provides an overview of upcoming features and enhancements currently being designed and developed for KDB-X.

Disclaimer

Statements regarding future releases, updates, or enhancements are forward-looking and subject to change without notice. Actual results may differ materially due to various factors, including changes in market conditions, technological advancements, and customer feedback. We do not undertake any obligation to update these forward-looking statements.

KDB-X continues to evolve as a unified, developer-first data platform for real-time analytics and AI. The roadmap below outlines broad themes that guide our ongoing development, balancing accessibility, extensibility, and AI-native evolution with the reliability and performance that define KX products.

Please send us feedback on preview@kx.com and join our community channels to stay connected to product updates as we expand the platform.

Theme	17 Nov 2025 KDB-X GA	Roadmap / Under Consideration
Accessibility and Developer Experience	- General availability (GA) of KDB-X, a developer centric platform from KX. - Fully-featured Community Edition license available for free personal and commercial use. Sign up for the Community Edition. - Curated tutorials and how-to guides designed to help users explore new features through structured use-cases for q and Python developers. - Developer Center launched to provide a KDB-X centered experience for all developer resources (docs, tutorials, blogs, integrations, and more) including new Single Sign-On (SSO) support for the KX Academy and KX community forums. - Streamlined single command installation for all KDB-X components. - VSCode IDE support for KDB-X including first-time installation.	- A suite of new and enhanced developer tools distributed as KX modules for all q users: linter, profiler, debugger, unit testing, qdocs generation, code coverage, visualization. - IDE and editor-agnostic support for developer tooling via LSP (Language Server Protocol). - Integration with KX MCP to accelerate natural language (NL) development. - NL query building, agentic workflows, and AI-assisted coding through q-trained LLMs to expand accessibility to non-q developers and AI users. - Expanded in-browser tutorials and documentation enabling live code snippets for a developer-first docs experience using WASM.
Extensibility and Modules	- Native module support introducing new primitives to modernize library handling and safety through import aliasing. - First release of KDB-X modules. Check out our modules.	- Extensive set of open-source KX modules for users. - Best practices and tooling for module developers. - Versioning and dependency management. - Official KX repository to host and facilitate discovery of KX and community-contributed modules.
Interoperability and Open Data	- Native support for executing queries on Parquet files, leveraging partition and row-group pruning to minimize processed data. - KDB-X now integrates with KX Dashboards, enabling real-time data visualization. - Built-in Python, SQL, and PostgreSQL wire support to help new users get started quickly with KDB-X using familiar tools and languages.	- Deeper support for Parquet and open table formats like Iceberg. - Generalization of query engine support for additional file formats. - Expanded object storage integration for read/write patterns. - Enhanced modules for interoperability with third-party software (for example, Kafka, Arrow, Solace).
Language and Performance	- Full code compatibility with the latest kdb+ and PyKX versions. - Embedded support for rlwrap to give users immediate productivity in the terminal experience, without requiring new users to install additional software. - Significant enhancements for datatype conversions within KDB-X Python (PyKX).	- Multi-level partitioning support for the native kdb file format (concept introduced in the support for Parquet virtual tables). - Multi-root databases with mixed partitioning styles. - Unified architecture support using virtual tables to enable qSQL gateway patterns. - IPC optimizations to eliminate unnecessary serialization and deserialization steps.
Data and AI Services	- Integrated AI libraries providing vector search, time-series similarity, and hybrid filtering for structured and unstructured data. - MCP Server integration, enabling natural language AI querying and extensibility with KDB-X.	- Additional previews for services that lower the barrier to entry for users integrating AI and time-series workloads. - Initial target services to provide standard reference architectures across real-time and historical use cases with both structured and unstructured data. - Further exploration of AI-focused features such as GPU acceleration to speed up compute-heavy operations like asof joins, matrix multiplication, and vector similarity search.

Keep checking back to see what is new in our roadmap. If you have any suggestions or requests, reach out to our KX Slack Community.