KDB-X

KDB-X is the next evolution of kdb+, a columnar database and programming language that has been the standard for high-frequency time-series analytics in capital markets for over 30 years. It is built on the same high-performance compute engine as kdb+ but redesigned for accessibility, extensibility, and AI readiness. KDB-X targets developers and quants building real-time, data-intensive, and AI-driven applications—particularly in finance—who need to unify streaming, historical, and vector workloads without stitching together multiple tools. It is available in Public Preview with a free Community Edition that permits commercial use, and it supports Python, SQL, and q from a single runtime, along with native GPU acceleration, Parquet and other open formats, and modular module management. KDB-X is backward compatible, so existing q/kdb+ and PyKX code runs without changes.

KDB-X combines time-series analytics, vector search, and GPU-accelerated compute in one runtime. Its native GPU acceleration delivers 10x to 25x performance improvements on joins, aggregations, backtesting, risk simulation, and model scoring, with near-linear scaling across multiple GPUs. In TSBS benchmarking against QuestDB, ClickHouse, InfluxDB, and TimeScaleDB, KDB-X won 58 of 64 scenarios across aggregation, filtering, and group-by workloads; ClickHouse was up to 1,100x slower on worst-case queries. KDB-X achieved these results using just 4 threads (1.5% of total CPU capacity) and 16 GB of memory (8% of system resources), while competitors required full hardware utilization. It also supports dual-mode analytics for structured and unstructured data, AI libraries with natural language processing, and multi-cloud, hybrid, and on-prem deployments.

KDB-X competes directly with QuestDB, an open-source time-series database that offers SQL familiarity and lower initial cost but lacks enterprise-grade performance guarantees, professional support, and advanced security. KX holds 17 STAC-M3 world records for tick-level analytics, and KDB-X extends that performance into modern AI pipelines. While QuestDB suits basic workloads and smaller projects, KDB-X provides guaranteed performance at scale, comprehensive support, and long-term stability. Other competitors include ClickHouse, InfluxDB, and TimeScaleDB, which KDB-X outperformed in TSBS benchmarks. KDB-X is positioned as a unified platform that eliminates the complexity of fragmented systems, turning static research workflows into real-time decision engines.

The honest trade-off: KDB-X is free to use commercially only under the Community Edition, which has usage limits; beyond that, a paid license is required. It is not fully open-source, unlike QuestDB, and its ecosystem is still maturing—modules and some developer tooling are in iterative releases. Organizations that need simple SQL-based time-series storage without real-time or AI capabilities may find QuestDB or InfluxDB more straightforward. Additionally, while KDB-X is backward compatible, teams new to q face a learning curve, and the platform's full power is best realized in high-frequency, large-volume environments where its performance and efficiency advantages matter most.

Free to use (even commercially) under the KDB-X Community Edition, which has usage limits; paid licenses required for full enterprise use beyond those limits.