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KDB-X Public Preview: The next-gen kdb+ is here

Raji Narayanan

Author

Raji Narayanan

Head of product for KDB-X

Key Takeaways

  1. KDB-X is the next evolution of kdb+ and now available in Public Preview
  2. KDB-X combines the functionality of kdb+, Python, SQL, and AI features into one cohesive system
  3. KDB-X delivers a streamlined developer experience with simplified installation and improved documentation
  4. Developers are invited to test, give feedback, and help shape what's next

For years, kdb+ has proven itself in the most demanding data environments, including Capital Markets, where every nanosecond impacts execution speed and trading P&L. As head of product for KDB-X, what excites me most is that we now get to build on that same foundation, towards our vision of accessibility, extensibility, and interoperability for modern development teams.

We asked for your input on bringing this vision to life, and your feedback was sharp and unfiltered, pointing to everything from onboarding friction to gaps in ecosystem integration. We listened and have been heads-down working on these pain points. Today, I am excited to announce that KDB-X, the next generation of kdb+ is available in Public Preview.

KDB-X evolves the proven kdb+ engine, delivering significant advances toward the vision we’ve outlined together. This first Public Preview release gives you the free Community Edition with usage limits.

This release focuses on the accessibility improvements you flagged, removing barriers that made kdb+ difficult to discover, learn, and use. It also includes AI functionality that unlocks new use cases for time series and vector data.

KDB-X is the foundation for the broader transformation we outlined, with open-format integration, module management, and additional developer tooling included in future iterative feature releases.

Give it a try and let us know what you think.

What is KDB-X?

KDB-X is the next evolution of kdb+, built on the same high-performance compute engine but designed for accessibility, extensibility, and AI readiness, with full interoperability across open data stacks.

More specifically, KDB-X is a unified engine for developers building time-series and vector data systems at any scale. It integrates the functionality of kdb+ with Python, SQL, and AI features into a cohesive framework for building real-time, data-intensive, and AI-driven applications. This means developers can bring powerful analytics to their data and engineer AI applications without having to stitch together multiple disparate tools.

KDB-X is designed from the ground up to enable modular development patterns and ecosystem integrations that drive reuse and faster innovation. To support this, KDB-X will introduce language-level features that simplify the creation, loading, and maintenance of modules, as well as updated libraries and interfaces built on the module system.

KDB-X can be deployed locally or on private cloud instances and is designed to be backward compatible, so existing q/kdb+ and PyKX code works seamlessly.

Why should you care?

If you’re building data-intensive applications, you’ve likely hit these pain points: lagged analytics that slow down decision-making, complex workflows involving multiple tools just to process your data, and infrastructure costs that spiral as data volumes grow. Meanwhile, you’re sitting on untapped information that could drive better decisions if you could analyze it in real time.

We know developers have many options for high-performance data processing, from columnar databases to specialized time-series solutions to drop-in data processing libraries.

So, how is KDB-X different?

  1. KDB-X is uniquely both a programming language and a database. It enables you to ingest, query, and run complex analytical processing on massive volumes of data in real time, all within the same environment. Instead of extracting data to run calculations elsewhere, you build analytical logic directly where your data lives. This provides the performance you need for data-intensive workloads even in resource-constrained environments. Its columnar design and optimized architecture deliver fast analytics without requiring massive infrastructure.
  2. If you’re already a q/kdb+ expert, you know this architectural advantage has powered mission-critical applications in data-intensive industries, such as Capital Markets, for years. With KDB-X, we’ve taken that established foundation and made it accessible to developers who are not q experts with built-in Python and SQL interfaces. It allows you to build meaningful applications quickly, while still having the full power of q available when tackling complex challenges.
  3. For both new and experienced users, KDB-X integrates AI features, such as vector search and temporal search, natively into the system, allowing you to incorporate these into your development workflows rather than relying on separate systems.

As we add native support for Parquet and open table formats like Iceberg, KDB-X extends its programming language-plus-database model to distributed and lakehouse environments, enabling direct queries on object storage and simplifying integration with modern data infrastructure.

What’s available today

The KDB-X Public Preview includes:

  • Free Community Edition with usage limits lets you experiment and build without upfront costs.
  • Streamlined developer experience with improved documentation, getting-started tutorials, and simplified installation and configuration
  • AI library featuring vector search (q native HNSW and Flat) and time-series similarity search (non-transformed, no embedding required) for fast pattern matching on unstructured and time-series data
  • SQL support for developers who want to use familiar query syntax alongside q
  • Python support for seamless integration with your existing Python workflows and libraries

KDB-X Community Edition provides a solid foundation to explore and start building applications that combine high-performance time-series processing with AI functionality.

Note: This Public Preview is designed for development and testing, with production readiness at General Availability.

Building KDB-X together

This release focuses on accessibility, but it’s just the beginning. Early feedback from developers has been positive, particularly around the streamlined getting-started experience, performance of AI libraries, and backward compatibility with existing code/workflows. We’re committed to developing a collaborative roadmap with the community and releasing features iteratively to deliver on the KDB-X vision. Across all areas, we continue to focus on performance and scalability – from advanced partitioning to efficient filtering to enhanced inter-process communication.

Our roadmap development efforts focus on three key areas:

Accessibility

Extensibility

Interoperability

Additional developer tools that improve the day-to-day coding experience

Natural language experience to call functions and run queries

Process & data management that make it frictionless to operate and scale

Robust module management system that simplifies development and encourages code reuse

Advanced vector and time-series search

GPU acceleration opportunities

Native integration for open formats, enabling qSQL/SQL against Parquet

Curated ecosystem of integrations for security protocols, monitoring tools, and third-party integrations

We are developing these features in phases.

  • Currently in development: Native integration with open formats, module management, and AI functionality
  • In R&D with working prototypes: GPU acceleration, which we would love to test with interested design partners

Share your thoughts on our roadmap priorities and tell us what matters most to your use cases.

How do I get started?

Follow the steps below to get started.

Learn more by visiting our product page, then try KDB-X and tell us what you think. We want to know what works, what doesn’t, and what you need that’s missing. Your feedback helps us decide what to build next.

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