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Barcelona Supercomputing Center spinout lands funding from Peak XV to accelerate the development of the first open, multi-dimensional indexing layer for Delta Lake, Apache Iceberg and Apache Hudi.
Bellevue, WA – August 4, 2025: As enterprise data volumes explode and AI pipelines strain modern infrastructure, the open Lakehouse architecture has emerged as the new standard for analytics at scale. But while formats like Delta Lake, Apache Iceberg, and Apache Hudi are powerful, they come with a hidden tax: up to 90% of compute resources are wasted scanning irrelevant data, according to Databricks. Today Qbeast, the next-generation data optimization platform, announces a $7.6 million seed round to fix that.
The seed round was led by Peak XV’s Surge (formerly Sequoia Capital India), with participation from HWK Tech Investment and Elaia Partners. The new capital will fund team expansion, broaden product support across more analytics use cases, and double down on the company’s mission to make open data platforms faster, simpler, and more cost-efficient.
Born out of research at the Barcelona Supercomputing Center, Qbeast’s platform plugs directly into existing Delta, Iceberg, and Hudi tables and accelerates workloads by prioritizing just the data you need. Its multi-dimensional indexing can handle complex filters across columns like time, region, or customer segment – optimizing for both real-time and historical queries in a single table. Unlike traditional partitioning or sort orders that work in single dimensions, Qbeast enables simultaneous filtering across any combination of data attributes. And it integrates with popular compute engines like Spark, Databricks, Snowflake, DuckDB, and Polars without requiring teams to rewrite pipelines or adopt a new storage layer.
To lead the next chapter of the company’s growth, Srikanth Satya, a cloud infrastructure veteran with decades of experience at AWS and Microsoft Azure, has been appointed as Qbeast’s CEO. His deep technical expertise in cloud-native architecture and strategic leadership will steer Qbeast through its next phase of global expansion.
“Data teams shouldn’t have to choose between speed, cost, and openness,” said Satya. “We built Qbeast to make high-performance analytics simple and accessible, without locking organizations into proprietary systems. In a world where data is growing faster than ever, we’re here to ensure every company can turn that data into value on their own terms.”
Today’s data lakes are massive, but not smart – and this is where the technical challenge lies. Everyone’s storing their data in open formats, but compute costs are exploding and most queries are painfully slow. Qbeast solves this with drop-in indexing that delivers sub-second performance and cost savings, without locking you into a new stack. In production environments, Qbeast has already delivered query speedups of 2–6x and compute cost reductions of up to 70% for workloads in finance, healthcare, and retail.
“There is an undesirable compute cost hidden in the data layout that has been highly neglected by the market for data lakehouses,” shared Flavio Junqueira, CTO of Qbeast and co-creator of Apache ZooKeeper and Apache BookKeeper. “Our technology enables customers across verticals to reduce or even eliminate such costs in a manner that embraces the openness of the data lakehouse stack and that is both engine and format neutral.”
The team behind Qbeast includes heavy hitters in distributed systems and open data. The company’s core technology is rooted in research conducted by Cesare Cugnasco, CSO of Qbeast and Paola Pardo during their time at the Barcelona Supercomputing Centre, where breakthrough work in multi-dimensional indexing laid the foundation for today’s platform. Unlike closed platforms that require vendor lock-in or significant rewrites, Qbeast plays natively with the tools data teams already use, serving organizations across finance, retail, healthcare and beyond — any team using open formats to power analytics, AI, or business intelligence at scale.
“We believe every organization, not just the tech elite, should be able to extract value from their data without incurring massive cloud costs or hiring a team of engineers to tune performance,” added Satya.
“We believe Qbeast is solving a fundamental challenge in the modern data stack. In a context of data volume explosion, their multi-dimensional indexing layer has the potential to become critical for every company moving to a lakehouse model”, said Juan Santamaría, CEO and Managing Partner at HWK TechInvestment.
“By empowering enterprises to unlock more value from their data with less complexity and expense, Qbeast aims to become the cornerstone indexing layer for modern data stacks”. said Sébastien Lefebvre, Partner & Deep Tech Investor at Elaia.
Looking ahead, Qbeast plans to extend its platform with auto-tuning, adaptive indexing, and deeper engine support across cloud providers and use cases. The goal: to become the default indexing layer for open Lakehouse architectures and unlock a future where data-driven innovation doesn’t come at the cost of performance, scalability, or sanity.
About Qbeast
Qbeast is a data infrastructure company transforming analytics performance for the Lakehouse era. Initiated with research conducted by our founding team at BSC, Qbeast blends cutting-edge academic innovation with practical industry expertise to deliver multi-dimensional indexing for modern open data platforms, including Delta Lake, Apache Iceberg and Apache Hudi. The company exists to make open Lakehouse platforms faster, cost efficient, and easier to use.
Qbeast’s leadership team includes world-class experts in cloud infrastructure, distributed systems, and data indexing. CEO Srikanth Satya brings decades of experience building cloud-scale platforms at AWS and Azure. CTO Flavio Junqueira is a renowned distributed systems researcher and co-creator of open-source projects based on distributed consensus such as Apache ZooKeeper and Apache BookKeeper. Qbeast’s core technology is rooted in research conducted by Cesare Cugnasco and Paola Pardo during their time at the Barcelona Supercomputing Centre (BSC).
About Peak XV
Peak XV (formerly Sequoia Capital India & SEA) is a leading venture capital firm investing across India, Southeast Asia and beyond. Peak XV (pronounced Peak Fifteen) was the name used for Mount Everest before it was called that. Over the last 17 years of our operations in the region, Peak XV has grown to manage over USD 9 billion in capital across 13 funds and invested in over 400 companies. To know more, please visit: www.peakxv.com.
About HWK
HWK is a Madrid-based VC firm backing ambitious tech founders across Europe. We invest in early-stage companies building foundational technologies in fields like cybersecurity, AI, and observability.They focus their investment on high-conviction investments with long-term support, helping founders scale from pre-seed to market leadership. Learn more: http://www.hwk.es • @HWK_VC
About Elaia
Elaia is a European top-tier VC firm with a strong tech DNA. We back tech disruptors with global ambition from early stage to growth development. For the past 20 years, our commitment has been to deliver high performance with values. They have been an active partner in over 100 startups including success stories such as Criteo (Nasdaq), Orchestra Networks (acquired by Tibco), Volterra (acquired by F5), Mirakl (valued $3.5B in Series E) and Shift Technology (valued $1B+ in Series D). Learn more http://www.elaia.com • @Elaia_Partners
About Barcelona Supercomputing Center – Centro Nacional de Supercomputación (BSC-CNS):
BSC is the leading supercomputing center in Spain. It specializes in high-performance computing. It has a dual role: providing infrastructure and a supercomputing service for Spanish and European scientists, and generating knowledge and technology to be transferred to society. It is a member of the top-level European research infrastructure PRACE (Partnership for Advanced Computing in Europe) and coordinates the Spanish Supercomputing Network (RES). BSC is a public consortium owned by the Spanish Government Ministry of Science and Innovation (60%), the Catalan Government Department of Research and Universities (30%) and the Polytechnic University of Catalonia (10%).
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Image source: Qbeast.io
