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Meet e6data: The Kubernetes-native data compute engine promising massive cost savings
e6data's lakehouse compute engine promises 5x better query performance on the heaviest workloads with 50% lower total cost of ownership.
The approach works, but when faced with high load, concurrency, or complexity of heavy workloads, these centralized, monolithic components become a source of resource inefficiency or even a single point of failure. To address this gap and give enterprises a better way to handle heavy workloads, he and the e6data team, which has worked on several commercial and open-source data projects, reimagined the compute engine architecture by disaggregating it with decentralized components that can independently and granularly scale in response to various forms of load. Globally, the total addressable market (TAM) for data and AI solutions is slated to touch $230 billion in 2025, with 60% of CXOs planning to increase their spending over the next year alone.
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