Voltron Data provides Theseus, a GPU-accelerated SQL engine designed for processing petabyte-scale data without the need for indexing or data movement. It enables enterprises to significantly reduce query times, server counts, and operational costs, making it ideal for large-scale ETL and machine learning preprocessing tasks.
Funding
$110M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
WCFounders
Product
Problem
Enterprises face challenges in processing petabyte-scale data efficiently, often requiring extensive indexing, data movement, and large server deployments, leading to increased query times and operational costs. Existing solutions struggle to provide the necessary performance and scalability for large-scale ETL and machine learning preprocessing tasks without significant infrastructure investments.
Solution
Theseus, by Voltron Data, is a GPU-accelerated SQL engine designed to process petabyte-scale data without indexing or data movement. It enables enterprises to accelerate data analytics by leveraging the massive parallelism of GPUs, significantly reducing query times and server counts. Theseus integrates into existing data stacks, supporting open-source standards like Arrow and Ibis, allowing users to switch between engines like DuckDB and Snowflake without code changes. The engine is suitable for tabular machine or log data and can be deployed on-premise or in the cloud where Kubernetes is supported.
Target Audience
The primary target audience includes enterprises in financial services and cybersecurity that manage large-scale data platforms and require high-performance data processing for prediction, simulations, strategic planning, and threat detection.
Features
- GPU-accelerated SQL engine for petabyte-scale data processing
- No indexing or data movement required
- Maximizes GPU utilization and extends the life of existing GPUs
- Supports open-source standards like Arrow, Ibis, Substrait, and ADBC
- Compatible with various data formats, including CSV, Parquet, ORC, and Avro
- Can be deployed on-premise or in the cloud with Kubernetes support (GKE, EKS, AKS)
- Integrates with data warehouses like Snowflake
- Supports multiple SQL dialects, including PostgreSQL and Standard SQL