e6data has announced a $10 million Series A funding round as it seeks to tap into firms looking to trim the cost of analyzing their own data.

The data lakehouse startup says it is aiming to "level the playing field" for customers by negating the "immense pricing power" a handful of vendors in the space currently enjoy, due to what it characterizes as various "new forms of compute ecosystem lock-ins" at different layers of the data stack.

In today's digital-first landscape, said e6data, enterprises rely on powerful data and AI capabilities to fuel innovation, enhance customer experiences, and optimize operations. However, they are set to spend an estimated $100 billion in 2024 on data intelligence platforms to derive value from their own data.

Focused on this data compute spend, e6data says it aims to halve that bill. Its Series A funding round was led by Accel Partners, with participation from Beenext and others.

"The rapid increase in spending has made data intelligence platforms the second largest IT spending category, behind only cloud spend, for operational systems and application infrastructure," said Vishnu Vasanth, co-founder and CEO of e6data. "It's fuelling the meteoric rise of data warehouse and data lakehouse companies such as Snowflake and Databricks, and the rapid growth of corresponding offerings from AWS, Azure, and Google Cloud."

However, as the spending grows, concerns over whether businesses are achieving a return on investment (RoI) are reaching "boiling point," he adds. "Legitimate RoI concerns stand in the way of enterprises realizing the full potential of data and AI." He says organizations cannot freely move lakehouse table formats, data catalogs, compute providers, and cloud providers without "adverse" price-performance impacts, the need for data movement, and "cumbersome" application migrations.

To address the challenges, e6data has developed a "compute engine" for data intelligence platforms that helps enterprises amplify RoI on their existing platforms and architectures, and "escape" ecosystem lock-ins. And it is promised there will be "zero friction" to adoption, with zero data movement, zero application migration, and zero downtime.

e6data is offering its Lighthouse Customer Program as a managed service to enterprise customers, complete with production support and professional services.

e6data says data lakehouses and warehouses use, at their core, distributed compute engines, whether open source or vendor-backed, for every form of processing spanning ingestion, transformation, dashboards, reports, ML model training and inference, as well as RAG-based generative AI applications.

However, it maintains that existing compute engines are built on "monolithic architectures" with centralized components for most aspects of a query or job's life cycle. This creates challenges with respect to cost, performance, concurrency handling, and uptime, says e6data, particularly on compute-intensive heavy workloads that enterprises increasingly encounter as they operate at production scale.

e6data promises it can address these challenges with a new engine architecture and distributed processing model that is disaggregated, decentralized, and Kubernetes-native. It claims its engine outperforms leading commercial and open source solutions across "real-world heavy workloads" and popular benchmarks, using a "truly format-neutral approach" that negates ecosystem lock-in. e6data says it has already signed up publicly listed Fortune 500 enterprises, as well as "high growth" companies as customers. But the proof of the pudding is in the eating, as they say.