Qbeast Receives $7.6M in Seed Funding to Assist Open Data Platforms Scale

Qbeast, a data optimization platform born from Barcelona Supercomputing Center research, has secured $7.6 million in seed funding led by Peak XV's Surge to accelerate open data platform performance.

The company's innovative multi-dimensional indexing technology integrates seamlessly with existing Delta, Iceberg, and Hudi tables, optimizing complex queries across multiple data attributes simultaneously. Unlike traditional single-dimension partitioning, Qbeast enables simultaneous filtering across any combination of columns including time, region, and customer segments while maintaining compatibility with popular engines.

• Works natively with Spark, Databricks, Snowflake, DuckDB, and Polars without requiring pipeline rewrites
• Accelerates both real-time and historical queries in unified tables across finance, retail, and healthcare sectors
• Plans to expand with auto-tuning and adaptive indexing to become the default indexing layer for open Lakehouse architectures
• Eliminates vendor lock-in while reducing cloud costs and performance tuning complexity for data teams