Thunderduck Inc.

Thunderduck redefines data management with a modular, high-performance approach. Key features: • Isolated data engine per process • Federated querying across diverse sources • Sub-second query response on large datasets • Flexible deployment: cloud, on-premise, BYOC • Pre-execution query cost transparency This platform excels in scenarios requiring dedicated, resource-efficient data access for numerous independent operations. It eliminates the need for complex ETL processes by allowing direct SQL queries across Postgres, BigQuery, Iceberg, and S3 files, unifying disparate data landscapes without data movement. The architecture is designed for speed, ensuring minimal latency between a data request and its answer, even for terabytes of information. Thunderduck significantly reduces operational overhead and cost compared to traditional data warehouse setups, particularly for workloads characterized by many small, parallel queries. It provides enterprise-grade governance and security, alongside self-managing capabilities for data assets like Iceberg tables. Teams gain full data sovereignty, maintaining control over their data within their own cloud or data center environment. Ideal for development teams, data analysts, and applications needing rapid, scalable, and cost-effective data access. It supports various interfaces including SQL, Metabase, Superset, JDBC, SQLAlchemy, and REST, making it a versatile component for modern data stacks that prioritize efficiency and direct data interaction.