Unlock faster data processing for smarter decisions
Voltron Data offers a new way to design and build composable data systems for enterprises and government agencies. Voltron Data has built the foundational software to unlock the next generation of accelerated computing that underpins modern AI applications. Founded in 2021 and headquartered in Mountain View, California, Voltron Data’s core solution—Theseus —is a SQL query engine that can enable enterprises to process petabyte-scale data faster and at a lower cost than traditional CPU-based systems.
Theseus, is an advanced distributed query engine designed to leverage full system hardware acceleration for petabyte-scale data processing. It's particularly notable for its capability to handle massive datasets by utilizing GPU hardware acceleration, which enables significantly faster processing times compared to traditional CPU-based systems.
We built this solution from the ground up to integrate seamlessly with modern data platforms through open, modular standards like Arrow, Ibis, and Substrait, allowing for a flexible and scalable deployment in diverse IT environments. It supports a wide range of hardware, including NVIDIA GPUs and ARM processors, enhancing its adaptability and performance capabilities.
Key features of Theseus include its ability to perform analytics directly on raw data without the need for pre-indexing, making it suitable for real-time applications that require rapid data processing. It also facilitates the integration of data analytics and AI pipelines on the same GPU infrastructure, optimizing both energy consumption and reducing carbon footprint.
Theseus distinguishes itself by being highly composable and embeddable within enterprise data systems, offering a revenue-share model instead of traditional licensing fees. This model allows partners to incorporate Theseus into their offerings and accelerate their go-to-market strategies while aligning costs directly with their revenue generation.
Overall, Theseus represents a significant step forward in the field of data analytics by addressing the limitations of current big data systems and enhancing the capability to handle the increasing demands of AI-driven analytics.